4,089 results match your criteria Computer Methods and Programs in Biomedicine [Journal]


Deep learning and SURF for automated classification and detection of calcaneus fractures in CT images.

Comput Methods Programs Biomed 2019 Apr 12;171:27-37. Epub 2019 Feb 12.

Institute of Cognitive Neuroscience, National Central University, Jhongli County, Taoyuan City, Taiwan. Electronic address:

Background And Objectives: The calcaneus is the most fracture-prone tarsal bone and injuries to the surrounding tissue are some of the most difficult to treat. Currently there is a lack of consensus on treatment or interpretation of computed tomography (CT) images for calcaneus fractures. This study proposes a novel computer-assisted method for automated classification and detection of fracture locations in calcaneus CT images using a deep learning algorithm. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.006DOI Listing

Polymorph segmentation representation for medical image computing.

Comput Methods Programs Biomed 2019 Apr 21;171:19-26. Epub 2019 Feb 21.

Laboratory for Percutaneous Surgery, School of Computing, 557 Goodwin Hall, Queen's University, K7L 2N8, Kingston, Ontario, Canada.

Background And Objective: Segmentation is a ubiquitous operation in medical image computing. Various data representations can describe segmentation results, such as labelmap volumes or surface models. Conversions between them are often required, which typically include complex data processing steps. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.011DOI Listing

Human age prediction based on DNA methylation of non-blood tissues.

Comput Methods Programs Biomed 2019 Apr 19;171:11-18. Epub 2019 Feb 19.

Digital Technologies Research Centre, National Research Council Canada, Ottawa, Ontario K1A 0R6, Canada. Electronic address:

Background And Objective: The study of human aging contributes to disease prevention, treatment and life extension. Recently, epigenetics studies have evidenced that there is a close association between DNA methylation and human ages. A quantitatively statistical modeling between DNA methylation and ages could predict the person's age more accurately. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.010DOI Listing
April 2019
1.897 Impact Factor

A hierarchical method based on weighted extreme gradient boosting in ECG heartbeat classification.

Comput Methods Programs Biomed 2019 Apr 20;171:1-10. Epub 2019 Feb 20.

School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China. Electronic address:

Background And Objective: Electrocardiogram (ECG) is a useful tool for detecting heart disease. Automated ECG diagnosis allows for heart monitoring on small devices, especially on wearable devices. In order to recognize arrhythmias automatically, accurate classification method for electrocardiogram (ECG) heartbeats was studied in this paper. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.005DOI Listing

Semi-automatic and robust determination of dental arch form in dental cone-beam CT with B-spline approximation.

Comput Methods Programs Biomed 2019 Apr 25;172:95-101. Epub 2019 Feb 25.

Department of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil Songpa-Gu, Seoul 05505, Republic of Korea; Department of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil Songpa-Gu, Seoul 05505, Republic of Korea. Electronic address:

Background And Objective: The dental arch form is generally used as a base for planning orthodontic treatments. It is, therefore, vital to determine the proper individual dental arch form for more accurate orthodontic treatment. We aimed to develop and validate a robust algorithm for semi-automatic determination of the dental arch form in dental cone-beam CT (CBCT) images with the cubic B-spline approximation. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.013DOI Listing

Human identification using a new matching Pursuit-based feature set of ECG.

Comput Methods Programs Biomed 2019 Apr 13;172:87-94. Epub 2019 Feb 13.

Graduated from Department of Biomedical Engineering, Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran. Electronic address:

Background And Objective: In recent years, many attempts have been made to design reliable systems for identifying individuals using biometrics. Electrocardiogram (ECG) biometric is one of the newest methods that not only offers unique characteristics of individuals for human identification, but also the possibility of counterfeiting it is negligible. In this paper, our objective was to develop an identification system using a non-fiducial one-lead ECG feature set based on a sparse algorithm. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.009DOI Listing

Development of a new theoretical model for blood-CNTs effective thermal conductivity pertaining to hyperthermia therapy of glioblastoma multiform.

Comput Methods Programs Biomed 2019 Apr 13;172:79-85. Epub 2019 Feb 13.

Department of Mechanical Engineering, University of West Attica, 12210 Athens, Greece. Electronic address:

Background And Objective: The present study deals with the hyperthermia therapy, which is the type of treatment in which tissues are exposed to high temperatures in order to destroy cancer cells with minimal injury to healthy tissues. In particular, it focuses on glioblastoma multiform, which is the most aggressive cancer that begins within the brain. Conventional treatments display limitations that can be overcome by using nanoparticles for targeted heating. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.008DOI Listing
April 2019
1 Read

Breast tumor localization using skin surface temperatures from a 2D anatomic model without knowledge of the thermophysical properties.

Comput Methods Programs Biomed 2019 Apr 12;172:65-77. Epub 2019 Feb 12.

School of Mechanical Engineering, Federal University of Uberlandia, Uberlandia 38408-100, Brazil. Electronic address:

Breast cancer is the second most common type of cancer among women after nonmelanoma skin cancer. Use of mammography, the main method to diagnose the disease, has several limitations in parts of the population. The primary goal of this work was to detect and localize the geometric centers of mammary tumors using only superficial temperatures of the breast skin. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.004DOI Listing

Association of respiratory integer and fractional-order models with structural abnormalities in silicosis.

Comput Methods Programs Biomed 2019 Apr 7;172:53-63. Epub 2019 Feb 7.

Biomedical Instrumentation Laboratory, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rio de Janeiro, Brazil; Laboratory of Clinical and Experimental Research in Vascular Biology (BioVasc), State University of Rio de Janeiro, Rio de Janeiro, Brazil. Electronic address:

Background And Objective: Integer and fractional-order models have emerged as powerful methods for obtaining information regarding the anatomical or pathophysiological changes that occur during respiratory diseases. However, the precise interpretation of the model parameters in light of the lung structural changes is not known. This study analyzed the associations of the integer and fractional-order models with structural changes obtained using multidetector computed tomography densitometry (MDCT) and pulmonary function analysis. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183160
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http://dx.doi.org/10.1016/j.cmpb.2019.02.003DOI Listing
April 2019
4 Reads

Effect of incremental feature enrichment on healthcare text classification system: A machine learning paradigm.

Comput Methods Programs Biomed 2019 Apr 1;172:35-51. Epub 2019 Feb 1.

Advanced Knowledge Engineering Center, Global Biomedical Technologies, Inc., Roseville, CA, USA. Electronic address:

Background And Objective: Healthcare tweets are particularly challenging due to its sparse layout and its limited character size. Compared to previous method based on "bag of words" (BOW) model, this study uniquely identifies the enrichment protocol and learns how semantically different aspects of feature selection such as BOW (feature F0), term frequency inverse document frequency (TF-IDF, feature F1), and latent semantic indexing (LSI, feature F2) when applied sequentially with classifier improves the overall performance.

Methods: To study this enrichment concept, our ML model is tested on two kinds of diverse data sets: (i) D1: Disease data with conjunctivitis, diarrhea, stomach ache, cough and nausea related tweets, and (ii) D2: WebKB4 dataset, while adapting three kind of classifiers (a) C1: support vector machine with radial basis function (SVMR), (b) C2: Multi-layer perceptron (MLP) and (c) C3: Random Forest (RF). Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183181
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http://dx.doi.org/10.1016/j.cmpb.2019.01.011DOI Listing
April 2019
4 Reads

Assessment of arterial baroreflex sensitivity by different computational analyses of pressure wave signals alone.

Comput Methods Programs Biomed 2019 Apr 2;172:25-34. Epub 2019 Feb 2.

First Department of Cardiology, Units of Biomedical Engineering (TGP, DS), Hypertension (KT), e-Cardiology (PD), Hippokration Hospital, Medical School, National and Kapodistrian University of Athens. 114 Vas. Sophias ave., Athens 11527, Greece.

Background And Objective: Baroreflex sensitivity (BRS) is an important indicator of the functionality of the arterial baroreceptors, and its assessment may have major research and clinical implications. An important requirement for its quantification is the continuous recording of electrocardiography (ECG) signal, so as to extract the RR interval, in parallel with continuous beat-to-beat blood pressure recording. We aimed to accurately calculate the RR Interval from pressure wave recordings per se, namely, the Pulse Interval (PI) using various arterial pulse wave analysis algorithms and to evaluate the precision and accuracy of BRS values calculated with the PI compared to BRS values calculated with the RR Interval. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.002DOI Listing

UMA-BCI Speller: An easily configurable P300 speller tool for end users.

Comput Methods Programs Biomed 2019 Apr 1;172:127-138. Epub 2019 Mar 1.

Departamento de Tecnología Electrónica, Universidad de Málaga, 29071 Málaga, Spain. Electronic address:

Background And Objective: Some neurodegenerative conditions can severely limit patients' capability to communicate because of the loss of muscular control. Brain-computer interfaces may help in the restoration of communication with these patients, bypassing the muscular activity, so that brain signals can be directly interpreted by a computer. There are many studies regarding brain-controlled spellers; however, these systems do not usually leap out of the lab because of technical and economic requirements. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.015DOI Listing

How can LVAD support influence ventricular energetics parameters in advanced heart failure patients? A retrospective study.

Comput Methods Programs Biomed 2019 Apr 23;172:117-126. Epub 2019 Feb 23.

National Research Council, Institute of Clinical Physiology (IFC-CNR), Via Palestro, 32, 00185 Rome, Italy. Electronic address:

Background And Objective: Here we present a retrospective analysis of six heart failure patients previously discussed at a multidisciplinary team meeting. Only three out of six patients underwent LVAD insertion as the most appropriate management option.

Methods: We sought to reproduce the baseline conditions of these patients on hospital admission using our cardiovascular software simulator (CARDIOSIM). Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183183
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http://dx.doi.org/10.1016/j.cmpb.2019.02.012DOI Listing
April 2019
4 Reads

Numerical simulation of magnetic drug targeting to a tumor in the simplified model of the human lung.

Comput Methods Programs Biomed 2019 Apr 2;172:11-24. Epub 2019 Feb 2.

School of Mechanical Engineering, Shiraz University, Shiraz, Iran.

Background: Magnetic drug targeting improves effectiveness of medicine application and reduces its side effects. In this method, drugs with magnetic core are released in the lung and they are steered towards the tumor by applying an external magnetic field. A number of researchers utilized numerical methods to study particle deposition in the lung, but magnetic drug delivery to the tumors in the human lung has not been addressed yet. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.001DOI Listing

Extraction of risk factors for cardiovascular diseases from Chinese electronic medical records.

Comput Methods Programs Biomed 2019 Apr 15;172:1-10. Epub 2019 Jan 15.

Language Technology Research Center, Harbin Institute of Technology, Integrated Building Room 803, 92 West Dazhi Street, Harbin 150001, Heilongjiang, China. Electronic address:

Background And Objective: Early prevention of cardiovascular diseases (CVDs) can effectively prevent later loss of health, and the detection of CVDs risk factors is a simple method to achieve early prevention. Personal health records play a prominent role in the field of health information extraction because of their factuality and reliability. This present study describes how to extract risk factors for CVDs from Chinese electronic medical records (CEMRs). Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.007DOI Listing
April 2019
1.897 Impact Factor

Online relative risks/rates estimation in spatial and spatio-temporal disease mapping.

Comput Methods Programs Biomed 2019 Apr 25;172:103-116. Epub 2019 Feb 25.

Department of Statistics, Computer Science and Mathematics, Public University of Navarre, Campus de Arrosadia, Pamplona 31006, Spain; InaMAT, Public University of Navarre, Campus de Arrosadia, Pamplona 31006, Spain. Electronic address:

Background And Objective: Spatial and spatio-temporal analyses of count data are crucial in epidemiology and other fields to unveil spatial and spatio-temporal patterns of incidence and/or mortality risks. However, fitting spatial and spatio-temporal models is not easy for non-expert users. The objective of this paper is to present an interactive and user-friendly web application (named SSTCDapp) for the analysis of spatial and spatio-temporal mortality or incidence data. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.02.014DOI Listing

A hospital wide predictive model for unplanned readmission using hierarchical ICD data.

Comput Methods Programs Biomed 2019 Feb 13. Epub 2019 Feb 13.

Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure Links 653, 9000, Ghent, Belgium.

Background And Objective: Hospitals already acquire a large amount of data, mainly for administrative, billing and registration purposes. Tapping on these already available data for additional purposes, aiming at improving care, without significant incremental effort and cost. This potential of secondary patient data is explored through modeling administrative and billing data, as well as the hierarchical structure of pathology codes of the International Classification of Diseases (ICD) in the prediction of unplanned readmissions, as a clinically relevant outcome parameter that can be impacted on in a quality improvement program. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183039
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http://dx.doi.org/10.1016/j.cmpb.2019.02.007DOI Listing
February 2019
6 Reads

An automated data verification approach for improving data quality in a clinical registry.

Comput Methods Programs Biomed 2019 Jan 31. Epub 2019 Jan 31.

College of Biomedical Engineering and Instrument Science, Zhejiang University, Zheda Road, 310027 Hanghzou, China; Key Laboratory for Biomedical Engineering, Ministry of Education, China. Electronic address:

Background And Objective: The quality of data is crucial for clinical registry studies as it impacts credibility. In the regular practice of most such studies, a vulnerability arises from researchers recording data on paper-based case report forms (CRFs) and further transcribing them onto registry databases. To ensure the quality of data, verifying data in the registry is necessary. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.012DOI Listing
January 2019
2 Reads

A model order reduction approach to create patient-specific mechanical models of human liver in computational medicine applications.

Comput Methods Programs Biomed 2019 Mar 11;170:95-106. Epub 2019 Jan 11.

PIMM, ENSAM ParisTech, CNRS, France.

Background And Objective: This paper focuses on computer simulation aspects of Digital Twin models in the medical framework. In particular, it addresses the need of fast and accurate simulators for the mechanical response at tissue and organ scale and the capability of integrating patient-specific anatomy from medical images to pinpoint the individual variations from standard anatomical models.

Methods: We propose an automated procedure to create mechanical models of the human liver with patient-specific geometry and real time capabilities. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.003DOI Listing

ECG based human identification using Second Order Difference Plots.

Comput Methods Programs Biomed 2019 Mar 16;170:81-93. Epub 2019 Jan 16.

Yildirim Beyazit University, Turkey. Electronic address:

Background And Objective: ECG is one of the biometric signals that has been studied in peer-reviewed over past years. The developments on the signal analysis methods show that the studies on the ECG would continue unabatedly. It has a common use on cardiac diseases with high rates of classification performances by integrating it with signal analysis methods. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.010DOI Listing
March 2019
1 Read

Speeding up the discovery of combinations of differentially expressed genes for disease prediction and classification.

Comput Methods Programs Biomed 2019 Mar 12;170:69-80. Epub 2019 Jan 12.

ECE Dept., Southern Illinois University, Carbondale, IL 62901, USA. Electronic address:

Background And Objective: Finding combinations (i.e., pairs, or more generally, q-tuples with q ≥ 2) of genes whose behavior as a group differs significantly between two classes has received a lot of attention in the quest for the discovery of simple, accurate, and easily interpretable decision rules for disease classification and prediction. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.004DOI Listing
March 2019
1 Read

Spinal cord detection in planning CT for radiotherapy through adaptive template matching, IMSLIC and convolutional neural networks.

Comput Methods Programs Biomed 2019 Mar 15;170:53-67. Epub 2019 Jan 15.

Federal University of Maranhão - UFMA Applied Computing Group - NCA Av. dos Portugueses, SN, Bacanga, São Luís, 65085-580, MA, Brazil. Electronic address:

Background And Objective: The spinal cord is a very important organ that must be protected in treatments of radiotherapy (RT), considered an organ at risk (OAR). Excess rays associated with the spinal cord can cause irreversible diseases in patients who are undergoing radiotherapy. For the planning of treatments with RT, computed tomography (CT) scans are commonly used to delimit the OARs and to analyze the impact of rays in these organs. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.005DOI Listing
March 2019
2 Reads

Concentration-dependent viscosity and thermal radiation effects on MHD peristaltic motion of Synovial Nanofluid: Applications to rheumatoid arthritis treatment.

Comput Methods Programs Biomed 2019 Mar 11;170:39-52. Epub 2019 Jan 11.

Mathematics Department, Faculty of Science, Imam Abdulrahman Bin Faisal University, Al-Dammam, Saudi Arabia.

Background And Objective: The biomedical fluid which fills the Synovial joint cavity is called Synovial fluid which behaves as in the fluid classifications to Non-Newtonian fluids. Also it's described as a several micrometers thick layer among the interstitial cartilages with very low friction coefficient. Consequently, the present paper opts to investigate the influence of the concentration-dependent viscosity on Magnetohydrodynamic peristaltic flow of Synovial Nanofluid in an asymmetric channel in presence of thermal radiation effect. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.001DOI Listing
March 2019
2 Reads

A probabilistic model for reducing medication errors: A sensitivity analysis using Electronic Health Records data.

Comput Methods Programs Biomed 2019 Mar 30;170:31-38. Epub 2018 Dec 30.

Graduate Institute of Biomedical Informatics, College of Medical Science & Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan; Department of Dermatology, Taipei Medical University Wan-Fang Hospital, Taipei, Taiwan. Electronic address:

Objectives: Medication-related clinical decision support systems have already been considered as a sophisticated method to improve healthcare quality, however, its importance has not been fully recognized. This paper's aim was to validate an existing probabilistic model that can automatically identify medication errors by performing a sensitivity analysis from electronic medical record data.

Methods: We first built a knowledge base that consisted of 2. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.033DOI Listing
March 2019
3 Reads

Prediction of fatty liver disease using machine learning algorithms.

Comput Methods Programs Biomed 2019 Mar 29;170:23-29. Epub 2018 Dec 29.

Graduate Institute of Biomedical Informatics, College of Medicine Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology(ICHIT), Taipei Medical University, Taipei, Taiwan; Department of Dermatology, Wan Fang Hospital, Taipei, Taiwan. Electronic address:

Background And Objective: Fatty liver disease (FLD) is a common clinical complication; it is associated with high morbidity and mortality. However, an early prediction of FLD patients provides an opportunity to make an appropriate strategy for prevention, early diagnosis and treatment. We aimed to develop a machine learning model to predict FLD that could assist physicians in classifying high-risk patients and make a novel diagnosis, prevent and manage FLD. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.032DOI Listing
March 2019
1 Read
1.897 Impact Factor

A propagation-DNN: Deep combination learning of multi-level features for MR prostate segmentation.

Comput Methods Programs Biomed 2019 Mar 29;170:11-21. Epub 2018 Dec 29.

Biomedical and Multimedia Information Technology Research Group, School of Computer Science, University of Sydney, Sydney, Australia.

Background And Objective: Prostate segmentation on Magnetic Resonance (MR) imaging is problematic because disease changes the shape and boundaries of the gland and it can be difficult to separate the prostate from surrounding tissues. We propose an automated model that extracts and combines multi-level features in a deep neural network to segment prostate on MR images.

Methods: Our proposed model, the Propagation Deep Neural Network (P-DNN), incorporates the optimal combination of multi-level feature extraction as a single model. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183109
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http://dx.doi.org/10.1016/j.cmpb.2018.12.031DOI Listing
March 2019
14 Reads

Adaptive color deconvolution for histological WSI normalization.

Comput Methods Programs Biomed 2019 Mar 15;170:107-120. Epub 2019 Jan 15.

Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.

Background And Objective: Color consistency of histological images is significant for developing reliable computer-aided diagnosis (CAD) systems. However, the color appearance of digital histological images varies across different specimen preparations, staining, and scanning situations. This variability affects the diagnosis and decreases the accuracy of CAD approaches. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.008DOI Listing
March 2019
1 Read

Prediction of sepsis patients using machine learning approach: A meta-analysis.

Comput Methods Programs Biomed 2019 Mar 26;170:1-9. Epub 2018 Dec 26.

Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan; Department of Dermatology, Wan Fang Hospital, Taipei, Taiwan; TMU Research Center of Cancer Translational Medicine, Taipei, Taiwan.

Study Objective: Sepsis is a common and major health crisis in hospitals globally. An innovative and feasible tool for predicting sepsis remains elusive. However, early and accurate prediction of sepsis could help physicians with proper treatments and minimize the diagnostic uncertainty. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.027DOI Listing
March 2019
2 Reads
1.897 Impact Factor

PROs in the wild: Assessing the validity of patient reported outcomes in an electronic registry.

Comput Methods Programs Biomed 2019 Jan 17. Epub 2019 Jan 17.

IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.

Background And Objectives: Collecting Patient-Reported Outcomes (PROs) is an important way to get first-hand information by patients on the outcome of treatments and surgical procedure they have undergone, and hence about the quality of the care provided. However, the quality of PRO data cannot be given for granted and cannot be traced back to the dimensions of timeliness and completeness only. While the reliability of these data can be guaranteed by adopting standard and validated questionnaires that are used across different health care facilities all over the world, these facilities must take responsibility to assess, monitor and ensure the validity of PROs that are collected from their patients. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.009DOI Listing
January 2019

An automatic diagnostic network using skew-robust adversarial discriminative domain adaptation to evaluate the severity of depression.

Comput Methods Programs Biomed 2019 Jan 17. Epub 2019 Jan 17.

The Intelligent Computing and Software Research Center, Information Science and Technology College, Beijing Normal University, 19 xinjiekou street, Beijing 100875, China.

Background And Objective: Deep learning provides an automatic and robust solution to depression severity evaluation. However, despite it is powerful, there is a trade-off between robust performance and the cost of manual annotation.

Methods: Motivated by knowledge evolution and domain adaptation, we propose a deep evaluation network using skew-robust adversarial discriminative domain adaptation (SRADDA), which adaptively shifts its domain from a large-scale Twitter dataset to a small-scale depression interview dataset for evaluating the severity of depression. Read More

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http://dx.doi.org/10.1016/j.cmpb.2019.01.006DOI Listing
January 2019

Semi-supervised encoding for outlier detection in clinical observation data.

Comput Methods Programs Biomed 2019 Jan 12. Epub 2019 Jan 12.

Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Boston, MA, USA; Partners Healthcare, Somerville, MA, USA. Electronic address:

Background And Objective: Electronic Health Record (EHR) data often include observation records that are unlikely to represent the "truth" about a patient at a given clinical encounter. Due to their high throughput, examples of such implausible observations are frequent in records of laboratory test results and vital signs. Outlier detection methods can offer low-cost solutions to flagging implausible EHR observations. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183075
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http://dx.doi.org/10.1016/j.cmpb.2019.01.002DOI Listing
January 2019
5 Reads

TAQIH, a tool for tabular data quality assessment and improvement in the context of health data.

Comput Methods Programs Biomed 2018 Dec 29. Epub 2018 Dec 29.

South Eastern Health and Social Care Trust, Upper Newtownards Road, Belfast, BT16 1RH, United Kingdom.

Background And Objectives: Data curation is a tedious task but of paramount relevance for data analytics and more specially in the health context where data-driven decisions must be extremely accurate. The ambition of TAQIH is to support non-technical users on 1) the exploratory data analysis (EDA) process of tabular health data, and 2) the assessment and improvement of its quality.

Methods: A web-based tool has been implemented with a simple yet powerful visual interface. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.029DOI Listing
December 2018
1 Read

Computer Aided Diagnosis System for multiple sclerosis disease based on phase to amplitude coupling in covert visual attention.

Comput Methods Programs Biomed 2019 Feb 24;169:9-18. Epub 2018 Nov 24.

Neuroscience & Neuroengineering Research Lab., Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, 16846-13114, Tehran, Iran. Electronic address:

Background And Objective: Computer Aided Diagnosis (CAD) techniques have widely been used in research to detect the neurological abnormalities and improve the consistency of diagnosis and treatment in medicine. In this study, a new CAD system based on EEG signals was developed. The motivation for the development of the CAD system was to diagnose multiple sclerosis (MS) disease during covert visual attention tasks. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.11.006DOI Listing
February 2019
1 Read

Geometrical features for premature ventricular contraction recognition with analytic hierarchy process based machine learning algorithms selection.

Comput Methods Programs Biomed 2019 Feb 27;169:59-69. Epub 2018 Dec 27.

Telecommunication and Aeronautic Engineering, São Paulo State University (UNESP), São João da Boa Vista, Brazil. Electronic address:

Background And Objective: Premature ventricular contraction is associated to the risk of coronary heart disease, and its diagnosis depends on a long time heart monitoring. For this purpose, monitoring through Holter devices is often used and computational tools can provide essential assistance to specialists. This paper presents a new premature ventricular contraction recognition method based on a simplified set of features, extracted from geometric figures constructed over QRS complexes (Q, R and S waves). Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.028DOI Listing
February 2019
6 Reads

Satisfaction and perceived usefulness with newly-implemented Electronic Health Records System among pediatricians at a university hospital.

Comput Methods Programs Biomed 2019 Feb 26;169:51-57. Epub 2018 Dec 26.

Pediatrics Department, College of Medicine, King Saud University, Riyadh, Saudi Arabia; Clinical Practice Guidelines Unit, Quality Management Department, King Saud University Medical City, Riyadh, Saudi Arabia; Research Chair for Evidence-Based Health Care and Knowledge Translation, King Saud University, Riyadh, Saudi Arabia.

Background: Apposite implementation of Electronic Health Records (EHR) is anchoring standards of care in healthcare settings by reducing long-run operational costs, improving healthcare quality, and enhancing patient safety.

Objective: This study aims to explore factors that might influence Pediatricians' satisfaction with an implemented EHR system and its perceived usefulness at a tertiary-care teaching hospital, Riyadh, Saudi Arabia.

Methods: A cross-sectional survey distributed to all physicians working in the pediatric department of King Saud University Medical City (KSUMC) in the period from June to November 2015, two months after the launch of the EHR system, internally branded as electronic system for integrated health information (eSiHi). Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.026DOI Listing
February 2019
3 Reads

Automatic quantification of the LV function and mass: A deep learning approach for cardiovascular MRI.

Comput Methods Programs Biomed 2019 Feb 12;169:37-50. Epub 2018 Dec 12.

CONICET - Departamento de Física Médica, Centro Atómico Bariloche, Av. Bustillo 9500, S. C. de Bariloche, Río Negro, 8400 Argentina; Comisión Nacional de Energía Atómica (CNEA) Argentina.

Objective: This paper proposes a novel approach for automatic left ventricle (LV) quantification using convolutional neural networks (CNN).

Methods: The general framework consists of one CNN for detecting the LV, and another for tissue classification. Also, three new deep learning architectures were proposed for LV quantification. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.002DOI Listing
February 2019
1 Read

An optimal strategy for prediction of sudden cardiac death through a pioneering feature-selection approach from HRV signal.

Comput Methods Programs Biomed 2019 Feb 7;169:19-36. Epub 2018 Dec 7.

Biomedical Engineering Department, School of Electrical Engineering, Payame Noor University of North Tehran, Tehran, Iran.

Background And Objective: Taking into consideration the critical importance of Sudden cardiac death (SCD), as it could be the first and the last heart condition to be diagnosed in a person while continuing to claim millions of lives around the world, prediction of sudden cardiac death has increasingly been regarded as a matter of substantive significance. This study does not seek to once again define features to predict and detect SCD, as there already has been adequate discussion addressing feature extraction in our previous works and other recent studies. What seems to be lacking attention is the need for an appropriate strategy to manage the extracted features to such an extent that the best classification is presented. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.12.001DOI Listing
February 2019
3 Reads

Automated real-time method for ventricular heartbeat classification.

Comput Methods Programs Biomed 2019 Feb 20;169:1-8. Epub 2018 Nov 20.

Instituto de Física Interdisciplinar y Sistemas Complejos, IFISC (CSIC-UIB), Campus Universitat de les Illes Balears, E-07122 Palma de Mallorca, Spain. Electronic address:

Background And Objective: In this work, we develop a fully automatic and real-time ventricular heartbeat classifier based on a single ECG lead. Single ECG lead classifiers can be especially useful for wearable technologies that provide continuous and long-term monitoring of the electrocardiogram. These wearables usually have a few non-standard leads and the quality of the signals depends on the user physical activity. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.11.005DOI Listing
February 2019
1 Read

What can millions of laboratory test results tell us about the temporal aspect of data quality? Study of data spanning 17 years in a clinical data warehouse.

Comput Methods Programs Biomed 2018 Dec 29. Epub 2018 Dec 29.

INSERM, Centre de Recherche des Cordeliers, UMRS 1138, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Hôpital Européen Georges Pompidou, Department of Medical Informatics, Assistance Publique - Hôpitaux de Paris (AP-HP), Université Paris Descartes, 20 rue Leblanc, 75015 Paris, France. Electronic address:

Objective: To identify common temporal evolution profiles in biological data and propose a semi-automated method to these patterns in a clinical data warehouse (CDW).

Materials And Methods: We leveraged the CDW of the European Hospital Georges Pompidou and tracked the evolution of 192 biological parameters over a period of 17 years (for 445,000 + patients, and 131 million laboratory test results).

Results: We identified three common profiles of evolution: discretization, breakpoints, and trends. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183070
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http://dx.doi.org/10.1016/j.cmpb.2018.12.030DOI Listing
December 2018
14 Reads

Deep into Patient care: An automated deep learning approach for reshaping patient care in clinical setting.

Comput Methods Programs Biomed 2019 Jan;168:A1-A2

Graduate Institute of Biomedical Informatics, College of Medicine Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Chair, Dept. of Dermatology, Wan Fang Hospital, Taipei, Taiwan. Electronic address:

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http://dx.doi.org/10.1016/j.cmpb.2018.11.007DOI Listing
January 2019
1 Read

compound.Cox: Univariate feature selection and compound covariate for predicting survival.

Comput Methods Programs Biomed 2019 Jan 27;168:21-37. Epub 2018 Oct 27.

Institute of Statistical Science, Academia Sinica, 128 Academia Road Sec.2, Nankang Taipei 115, Taiwan.

Background And Objective: Univariate feature selection is one of the simplest and most commonly used techniques to develop a multigene predictor for survival. Presently, there is no software tailored to perform univariate feature selection and predictor construction.

Methods: We develop the compound. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.10.020DOI Listing
January 2019
1 Read

Segmentation of skin lesions in dermoscopy images using fuzzy classification of pixels and histogram thresholding.

Comput Methods Programs Biomed 2019 Jan 20;168:11-19. Epub 2018 Nov 20.

Deustotech-LIFE Unit (eVIDA), University of Deusto Avda. Universidades, 24. 48007 Bilbao, Spain. Electronic address:

Background And Objective: To ensure proper functioning of a Computer Aided Diagnosis (CAD) system for melanoma detection in dermoscopy images, it is important to accurately detect the border of the lesion. This paper proposes a method developed by the authors to address this problem.

Methods: The algorithm for segmentation of skin lesions in dermoscopy images is based on fuzzy classification of pixels and subsequent histogram thresholding. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.11.001DOI Listing
January 2019
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Predicting combinative drug pairs via multiple classifier system with positive samples only.

Comput Methods Programs Biomed 2019 Jan 15;168:1-10. Epub 2018 Nov 15.

Department of Computer Science, The University of Hong Kong, Hong Kong, China. Electronic address:

Background And Objective: Due to the synergistic effects of drugs, drug combination is one of the effective approaches for treating complex diseases. However, the identification of drug combinations by dose-response methods is still costly. It is promising to develop supervised learning-based approaches to predict potential drug combinations on a large scale. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.11.002DOI Listing
January 2019
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Development of user-friendly tools for biomedical research and healthcare.

Comput Methods Programs Biomed 2018 Dec;167:A1

Graduate Institute of Biomedical Informatics, College of Medicine Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Chair, Dept. of Dermatology, Wan Fang Hospital, Taipei, Taiwan. Electronic address:

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183165
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http://dx.doi.org/10.1016/j.cmpb.2018.11.004DOI Listing
December 2018
3 Reads

A novel retinal vessel detection approach based on multiple deep convolution neural networks.

Comput Methods Programs Biomed 2018 Dec 30;167:43-48. Epub 2018 Oct 30.

Electrical and Electronics Engineering Department, Firat University, Elazig, Turkey.

Background And Objective: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detection is still a challenging problem due to variations in morphology of the vessels on noisy and low contrast fundus images. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.10.021DOI Listing
December 2018
3 Reads

Patient satisfaction with dermatology teleconsultation by using MedX.

Comput Methods Programs Biomed 2018 Dec 18;167:37-42. Epub 2018 Oct 18.

Graduate Institute of Biomedical Informatics, College of Medicine Science and Technology, Taipei Medical University, Taipei, Taiwan; School of Health Care Administration, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Department of Dermatology, Wan Fang Hospital, Taipei, Taiwan. Electronic address:

Background: The development of telecommunication has strongly affected comprehensive scientific disciplines, including medical sciences.

Objective: This study aims to assess the patient satisfaction of the teleconsultation system used for the consultation of dermatological follow-up care.

Methods: The study was performed cross sectional patient satisfaction survey method conducted between February and April 2017 to determine patient satisfaction using MedX teleconsultation system. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.10.015DOI Listing
December 2018
5 Reads
1.897 Impact Factor

BioSimulator.jl: Stochastic simulation in Julia.

Comput Methods Programs Biomed 2018 Dec 10;167:23-35. Epub 2018 Oct 10.

Department of Biomathematics, David Geffen School of Medicine at UCLA, USA. Electronic address:

Background And Objectives: Biological systems with intertwined feedback loops pose a challenge to mathematical modeling efforts. Moreover, rare events, such as mutation and extinction, complicate system dynamics. Stochastic simulation algorithms are useful in generating time-evolution trajectories for these systems because they can adequately capture the influence of random fluctuations and quantify rare events. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.09.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388686PMC
December 2018
2 Reads

Automated identification and grading of coronary artery stenoses with X-ray angiography.

Comput Methods Programs Biomed 2018 Dec 24;167:13-22. Epub 2018 Oct 24.

Intelligent Computing and Machine Learning Lab, School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China. Electronic address:

Background And Objective: X-ray coronary angiography (XCA) remains the gold standard imaging technique for the diagnosis and treatment of cardiovascular disease. Automatic detection and grading of coronary stenoses in XCA are challenging problems due to the complex overlap of different background structures with intensity inhomogeneities. We present a new computerized image based method to accurately identify and quantify the stenosis severity on XCA. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S01692607183072
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http://dx.doi.org/10.1016/j.cmpb.2018.10.013DOI Listing
December 2018
15 Reads

Automated 2D-3D quantitative analysis of corneal graft detachment post DSAEK based on AS-OCT images.

Comput Methods Programs Biomed 2018 Dec 9;167:1-12. Epub 2018 Oct 9.

Tej Kohli Cornea Institute, L. V. Prasad Eye Institute, Hyderabad, Telangana 500034, India.

Background And Objective: In current ophthalmological practices, assessment of graft condition post Descemet's stripping automated endothelial keratoplasty (DSAEK) is performed qualitatively using few (four) anterior-segment optical coherence tomography (AS-OCT) radial B-scans. From those scans, clinicians need to mentally synthesize the graft in 3D, and estimate its overall condition. In contrast, quantitative representation of 360° thickness profile would facilitate better visualization of graft condition, and hence medical decision making. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.10.003DOI Listing
December 2018
2 Reads

Initializing a hospital-wide data quality program. The AP-HP experience.

Comput Methods Programs Biomed 2018 Nov 9. Epub 2018 Nov 9.

DSI WIND, AP-HP, Paris, France; INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, Paris, France.

Background And Objectives: Data Quality (DQ) programs are recognized as a critical aspect of new-generation research platforms using electronic health record (EHR) data for building Learning Healthcare Systems. The AP-HP Clinical Data Repository aggregates EHR data from 37 hospitals to enable large-scale research and secondary data analysis. This paper describes the DQ program currently in place at AP-HP and the lessons learned from two DQ campaigns initiated in 2017. Read More

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http://dx.doi.org/10.1016/j.cmpb.2018.10.016DOI Listing
November 2018
10 Reads