4,051 results match your criteria Computer Methods and Programs in Biomedicine [Journal]


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:

View Article

Download full-text PDF

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

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

View Article

Download full-text PDF

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

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

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.11.001DOI Listing
January 2019

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

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.11.002DOI Listing
January 2019

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:

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183165
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.11.004DOI Listing
December 2018
1 Read

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

View Article

Download full-text PDF

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

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

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.015DOI Listing
December 2018
1 Read

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

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.09.009DOI Listing
December 2018

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

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183072
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.013DOI Listing
December 2018
2 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

View Article

Download full-text PDF

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

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

View Article

Download full-text PDF

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

Analyzing hedyotis diffusa mechanisms of action from the genomics perspective.

Comput Methods Programs Biomed 2018 Oct 31. Epub 2018 Oct 31.

School of Information Technology, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China. Electronic address:

Background And Objective: Hedyotis diffusa is an herb used for anti-cancer, anti-oxidant, anti-inflammatory, and anti-fibroblast treatment in the clinical practice of Traditional Chinese Medicine. However, its pharmacological mechanisms have not been fully established and there is a lack of modern scientific verification. One of the best ways to further understand Hedyotis diffusa's mechanisms of action is to analyze it from the genomics perspective. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607173066
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.019DOI Listing
October 2018
2 Reads

Artificial Intelligence in Clinical Implications.

Comput Methods Programs Biomed 2018 Nov;166:A1

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

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.022DOI Listing
November 2018

A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.

Comput Methods Programs Biomed 2018 Nov 5;166:99-105. Epub 2018 Oct 5.

School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. Electronic address:

Background And Objective: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods, remarkable progress in cancer research has been made based on gene expression data. At the same time, a growing amount of high-dimensional data has been generated, such as RNA-seq data, which calls for superior machine learning methods able to deal with mass data effectively in order to make accurate treatment decision. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183045
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.004DOI Listing
November 2018
2 Reads

Automated detection and classification of liver fibrosis stages using contourlet transform and nonlinear features.

Comput Methods Programs Biomed 2018 Nov 2;166:91-98. Epub 2018 Oct 2.

Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia; School of Medicine, Faculty of Health and Medical Sciences, Taylor's University, 47500 Subang Jaya, Malaysia.

Background And Objective: Liver fibrosis is a type of chronic liver injury that is characterized by an excessive deposition of extracellular matrix protein. Early detection of liver fibrosis may prevent further growth toward liver cirrhosis and hepatocellular carcinoma. In the past, the only method to assess liver fibrosis was through biopsy, but this examination is invasive, expensive, prone to sampling errors, and may cause complications such as bleeding. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183051
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.006DOI Listing
November 2018
5 Reads

Nutrition delivery, workload and performance in a model-based ICU glycaemic control system.

Comput Methods Programs Biomed 2018 Nov 11;166:9-18. Epub 2018 Sep 11.

Department of Intensive Care, Christchurch Hospital, Christchurch, New Zealand. Electronic address:

Background And Objective: Hyperglycaemia is commonplace in the adult intensive care unit (ICU), and has been associated with increased morbidity and mortality. Effective glycaemic control (GC) can reduce morbidity and mortality, but has proven difficult. STAR is a model-based GC protocol that uniquely maintains normoglycaemia by changing both insulin and nutrition interventions, and has been proven effective in controlling blood glucose (BG) in the ICU. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.09.005DOI Listing
November 2018
1 Read

Cascaded classifiers and stacking methods for classification of pulmonary nodule characteristics.

Authors:
Aydin Kaya

Comput Methods Programs Biomed 2018 Nov 3;166:77-89. Epub 2018 Oct 3.

Hacettepe University, Computer Engineering Department, 06800 Ankara, Turkey. Electronic address:

Background And Objectives: Detection and classification of pulmonary nodules are critical tasks in medical image analysis. The Lung Image Database Consortium (LIDC) database is a widely used resource for small pulmonary nodule classification research. This dataset is comprised of nodule characteristic evaluations and CT scans of patients. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.009DOI Listing
November 2018

Accurate liver vessel segmentation via active contour model with dense vessel candidates.

Comput Methods Programs Biomed 2018 Nov 4;166:61-75. Epub 2018 Oct 4.

School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea.

Background And Objective: The purpose of this paper is to propose a fully automated liver vessel segmentation algorithm including portal vein and hepatic vein on contrast enhanced CTA images.

Methods: First, points of a vessel candidate region are extracted from 3-dimensional (3D) CTA image. To generate accurate points, we reduce 3D segmentation problem to 2D problem by generating multiple maximum intensity (MI) images. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.010DOI Listing
November 2018

Diagnosis of urinary tract infection based on artificial intelligence methods.

Comput Methods Programs Biomed 2018 Nov 2;166:51-59. Epub 2018 Oct 2.

Department of Urology, Necmettin Erbakan University, Konya, Turkey.

Background And Objective: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflammation of other urinary tract organs. Since all of these infections have similar symptoms, it is difficult to identify the cause of primary infection. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183028
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.007DOI Listing
November 2018
12 Reads

Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images.

Comput Methods Programs Biomed 2018 Nov 21;166:39-49. Epub 2018 Sep 21.

Gaspard Monge Computer Science Laboratory, ESIEE-Paris, University Paris-Est Marne-la-Vallée, France. Electronic address:

Background And Objective: Nowadays, getting an efficient Brain Tumor Segmentation in Multi-Sequence MR images as soon as possible, gives an early clinical diagnosis, treatment and follow-up. The aim of this study is to develop a new deep learning model for the segmentation of brain tumors. The proposed models are used to segment the brain tumors of Glioblastomas (with both high and low grade). Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183090
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.09.007DOI Listing
November 2018
12 Reads

Fusion based Glioma brain tumor detection and segmentation using ANFIS classification.

Comput Methods Programs Biomed 2018 Nov 12;166:33-38. Epub 2018 Sep 12.

Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu 624001, India.

The detection of tumor regions in Glioma brain image is a challenging task due to its low sensitive boundary pixels. In this paper, Non-Sub sampled Contourlet Transform (NSCT) is used to enhance the brain image and then texture features are extracted from the enhanced brain image. These extracted features are trained and classified using Adaptive Neuro Fuzzy Inference System (ANFIS) approach to classify the brain image into normal and Glioma brain image. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.09.006DOI Listing
November 2018

Trends and characteristics of global medical informatics conferences from 2007 to 2017: A bibliometric comparison of conference publications from Chinese, American, European and the Global Conferences.

Comput Methods Programs Biomed 2018 Nov 27;166:19-32. Epub 2018 Aug 27.

Center for Medical Informatics, Peking University, 38 Xueyuan Rd, Haidian District, Beijing 100191, China; School of Medical Informatics and Engineering, Southwest Medical University, Luzhou, Sichuan, China. Electronic address:

Background: As the second-largest economy in the world, China has invested considerable financial and policy support into hospital informatization since health care reform in 2010. However, the results and experience of such investments have not been compared with relevant research and applications in the United States and Europe.

Objectives: From the perspective of professional conference proceedings, we comparatively analyzed the current situations, characteristics, hotspots, and trends of medical informatics (MI) development in China, the United States and Europe to help Chinese MI researchers and practitioners summarize their experiences and determine gaps compared to their American and European peers. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.08.017DOI Listing
November 2018
1 Read

Global optimal constrained ICA and its application in extraction of movement related cortical potentials from single-trial EEG signals.

Comput Methods Programs Biomed 2018 Nov 11;166:155-169. Epub 2018 Aug 11.

Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran. Electronic address:

Background And Objective: The constrained ICA (cICA) is a recent approach which can extract the desired source signal by using prior information. cICA employs gradient-based algorithms to optimize non convex objective functions and therefore global optimum solution is not guaranteed. In this study, we propose the Global optimal constrained ICA (GocICA) algorithm for solving the conventional cICA problems. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183058
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.07.013DOI Listing
November 2018
4 Reads

Towards an efficient and Energy-Aware mobile big health data architecture.

Comput Methods Programs Biomed 2018 Nov 4;166:137-154. Epub 2018 Oct 4.

Department of Information Systems and Security, College of IT, United Arab Emirates University, Al Ain 15551, UAE.

Background And Objectives: Mobile and ubiquitous devices are everywhere, generating an exorbitant amount of data. New generations of healthcare systems are using mobile devices to continuously collect large amounts of different types of data from patients with chronic diseases. The challenge with such Mobile Big Data in general, is how to meet the growing performance demands of the mobile resources handling these tasks, while simultaneously minimizing their consumption. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183056
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.008DOI Listing
November 2018
3 Reads

An improved support vector machine-based diabetic readmission prediction.

Comput Methods Programs Biomed 2018 Nov 12;166:123-135. Epub 2018 Oct 12.

School of Management Science and Engineering, Dalian University of Technology, Dalian 116023, PR China; Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH, United Kingdom.

Background And Objective: In healthcare systems, the cost of unplanned readmission accounts for a large proportion of total hospital payment. Hospital-specific readmission rate becomes a critical issue around the world. Quantification and early identification of unplanned readmission risks will improve the quality of care during hospitalization and reduce the occurrence of readmission. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183080
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.012DOI Listing
November 2018
7 Reads

Application of multiscale Poincaré short-time computation versus multiscale entropy in analyzing fingertip photoplethysmogram amplitudes to differentiate diabetic from non-diabetic subjects.

Comput Methods Programs Biomed 2018 Nov 2;166:115-121. Epub 2018 Oct 2.

Department of Emergency Medicine, E-Da Hospital, I-Shou University School of Medicine for International students, Kaohsiung, Taiwan. Electronic address:

Background And Objectives: Multiscale Poincaré (MSP) plots have recently been introduced to facilitate the visualization of time series of physiological signals. This study aimed at investigating the feasibility of MSP application in distinguishing subjects with and without diabetes.

Methods: Using photoplethysmogram (PPG) waveform amplitudes acquired from unilateral fingertip of non-diabetic (n = 34) and diabetic (n = 30) subjects, MSP indices (MSPI) of the two groups were compared using 1000, 500, 250, 100 data points. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.001DOI Listing
November 2018

Classification of auditory selective attention using spatial coherence and modular attention index.

Comput Methods Programs Biomed 2018 Nov 2;166:107-113. Epub 2018 Oct 2.

Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Minas Gerais, Av. Presidente Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG 31270-901, Brazil. Electronic address:

Background And Objective: Brain-Computer Interfaces (BCIs) based on auditory selective attention have been receiving much attention because i) they are useful for completely paralyzed users since they do not require muscular effort or gaze and ii) focusing attention is a natural human ability. Several techniques - such as recently developed Spatial Coherence (SC) - have been proposed in order to optimize the BCI procedure. Thus, this work aims at investigating and comparing two strategies based on spatial coherence detection: contralateral and modular classifiers. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.002DOI Listing
November 2018

Generating amorphous target margins in radiation therapy to promote maximal target coverage with minimal target size.

Authors:
Adam D Yock

Comput Methods Programs Biomed 2018 Nov 5;166:1-8. Epub 2018 Sep 5.

Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN 37232, USA. Electronic address:

Background And Significance: This work provides proof-of-principle for two versions of a heuristic approach that automatically creates amorphous radiation therapy planning target volume (PTV) margins considering local effects of tumor shape and motion to ensure adequate voxel coverage with while striving to minimize PTV size. The resulting target thereby promotes disease control while minimizing the risk of normal tissue toxicity.

Methods: This work describes the mixed-PDF algorithm and the independent-PDF algorithm which generate amorphous margins around a radiation therapy target by incorporating user-defined models of target motion. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.09.003DOI Listing
November 2018

mQC: A post-mapping data exploration tool for ribosome profiling.

Comput Methods Programs Biomed 2018 Oct 28. Epub 2018 Oct 28.

BioBix, Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modelling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, Ghent 9000, Belgium. Electronic address:

Background And Objective: Ribosome profiling is a recent next generation sequencing technique enabling the genome-wide study of gene expression in biomedical research at the translation level. Too often, researchers precipitously start trying to test their hypotheses after alignment of their data, without checking the quality and the general features of their mapped data. Despite the fact that these checks are essential to prevent errors and ensure valid conclusions afterwards, easy-to-use tools for visualizing the quality and overall outlook of mapped ribosome profiling data are lacking. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.018DOI Listing
October 2018

A systematic literature review and classification of knowledge discovery in traditional medicine.

Comput Methods Programs Biomed 2019 Jan 27;168:39-57. Epub 2018 Oct 27.

Department of Traditional Medicine, School of Traditional Medicine, Tehran University of Medical Science, Tehran, Iran.

Introduction And Objective: Despite the importance of machine learning methods application in traditional medicine there is a no systematic literature review and a classification for this field. This is the first comprehensive literature review of the application of data mining methods in traditional medicine.

Method: We reviewed 5 database between 2000 to 2017 based on the Kitchenham systematic review methodology. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183128
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.017DOI Listing
January 2019
4 Reads

Preface.

Comput Methods Programs Biomed 2018 Oct 16. Epub 2018 Oct 16.

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.014DOI Listing
October 2018

End-to-End syndrome differentiation of Yin deficiency and Yang deficiency in traditional Chinese medicine.

Comput Methods Programs Biomed 2018 Oct 16. Epub 2018 Oct 16.

Institute of Linguistics, Chinese Academy of Social Sciences, Beijing 100732, China; China Multilingual and Multimodal Corpora and Big Data Research Centre, Beijing 100089, China. Electronic address:

Background And Objective: Yin and Yang, two concepts adapted from classical Chinese philosophy, play a diagnostic role in Traditional Chinese Medicine (TCM). The Yin and Yang in harmonious balance indicate health, whereas imbalances to either side indicate unhealthiness, which may result in diseases. Yin-yang disharmony is considered to be the cause of pathological changes. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.10.011DOI Listing
October 2018

Modelling intestinal glucose absorption in premature infants using continuous glucose monitoring data.

Comput Methods Programs Biomed 2018 Oct 3. Epub 2018 Oct 3.

Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. Electronic address:

Background: Model-based glycaemic control protocols have shown promise in neonatal intensive care units (NICUs) for reducing both hyperglycaemia and insulin-therapy driven hypoglycaemia. However, current models for the appearance of glucose from enteral feeding are based on values from adult intensive care cohorts. This study aims to determine enteral glucose appearance model parameters more reflective of premature infant physiology. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183014
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.10.005DOI Listing
October 2018
6 Reads

The use of multimedia medical data and machine learning for various diagnoses.

Comput Methods Programs Biomed 2018 Oct;165: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, Taiwan;; Chair, Dept. of Dermatology, Wan Fang Hospital, Taipei, Taiwan. Electronic address:

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183139
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.09.008DOI Listing
October 2018
7 Reads

A facial expression controlled wheelchair for people with disabilities.

Comput Methods Programs Biomed 2018 Oct 18;165:89-105. Epub 2018 Aug 18.

University of Tunis, National Higher School of Engineers of Tunis, Laboratory of Signal Image and Energy Mastery (SIME), 5 Avenue Taha Hussein, P.O. Box 56, Tunis 1008, Tunisia.

Background And Objectives: In order to improve assistive technologies for people with reduced mobility, this paper develops a new intelligent real-time emotion detection system to control equipment, such as electric wheelchairs (EWC) or robotic assistance vehicles. Every year, degenerative diseases and traumas prohibit thousands of people to easily control the joystick of their wheelchairs with their hands. Most current technologies are considered invasive and uncomfortable such as those requiring the user to wear some body sensor to control the wheelchair. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607173154
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.013DOI Listing
October 2018
5 Reads

A virtual patient model for mechanical ventilation.

Comput Methods Programs Biomed 2018 Oct 10;165:77-87. Epub 2018 Aug 10.

Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand. Electronic address:

Background And Objectives: Mechanical ventilation (MV) is a primary therapy for patients with acute respiratory failure. However, poorly selected ventilator settings can cause further lung damage due to heterogeneity of healthy and damaged alveoli. Varying positive-end-expiratory-pressure (PEEP) to a point of minimum elastance is a lung protective ventilator strategy. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183015
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.004DOI Listing
October 2018
5 Reads

Transfer learning for classification of cardiovascular tissues in histological images.

Comput Methods Programs Biomed 2018 Oct 16;165:69-76. Epub 2018 Aug 16.

Universidad de León, Industrial and Informatics Engineering School, León, Spain.

Background And Objective: Automatic classification of healthy tissues and organs based on histology images is an open problem, mainly due to the lack of automated tools. Solutions in this regard have potential in educational medicine and medical practices. Some preliminary advances have been made using image processing techniques and classical supervised learning. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183052
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.006DOI Listing
October 2018
6 Reads

Prediction of paroxysmal Atrial Fibrillation: A machine learning based approach using combined feature vector and mixture of expert classification on HRV signal.

Comput Methods Programs Biomed 2018 Oct 10;165:53-67. Epub 2018 Aug 10.

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

Background And Objective: Paroxysmal Atrial Fibrillation (PAF) is one of the most common major cardiac arrhythmia. Unless treated timely, PAF might transform into permanent Atrial Fibrillation leading to a high rate of morbidity and mortality. Therefore, increasing attention has been directed towards prediction of PAF, to enable early detection and prevent further progression of the disease. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183048
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.07.014DOI Listing
October 2018
4 Reads

Fast unsupervised nuclear segmentation and classification scheme for automatic allred cancer scoring in immunohistochemical breast tissue images.

Comput Methods Programs Biomed 2018 Oct 10;165:37-51. Epub 2018 Aug 10.

Salah Azaiez Institute of Oncology, Morbid Anatomy Service, bd du 9 avril, Bab Saadoun, Tunis 1006, Tunisia. Electronic address:

Background And Objective: This paper presents an improved scheme able to perform accurate segmentation and classification of cancer nuclei in immunohistochemical (IHC) breast tissue images in order to provide quantitative evaluation of estrogen or progesterone (ER/PR) receptor status that will assist pathologists in cancer diagnostic process.

Methods: The proposed segmentation method is based on adaptive local thresholding and an enhanced morphological procedure, which are applied to extract all stained nuclei regions and to split overlapping nuclei. In fact, a new segmentation approach is presented here for cell nuclei detection from the IHC image using a modified Laplacian filter and an improved watershed algorithm. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183019
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.005DOI Listing
October 2018
6 Reads

The region of interest localization for glaucoma analysis from retinal fundus image using deep learning.

Comput Methods Programs Biomed 2018 Oct 8;165:25-35. Epub 2018 Aug 8.

Department of Computer Science and Engineering, Calcutta University Technology Campus, JD-2, Sector-III, Salt Lake, Kolkata 700098, India.

Background And Objectives: Retinal fundus image analysis without manual intervention has been rising as an imperative analytical approach for early detection of eye-related diseases such as glaucoma and diabetic retinopathy. For analysis and detection of Glaucoma and some other disease from retinal image, there is a significant role of predicting the bounding box coordinates of Optic Disc (OD) that acts as a Region of Interest (ROI).

Methods: We reframe ROI detection as a solitary regression predicament, from image pixel values to ROI coordinates including class probabilities. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.08.003DOI Listing
October 2018
1.900 Impact Factor

A supervised joint multi-layer segmentation framework for retinal optical coherence tomography images using conditional random field.

Comput Methods Programs Biomed 2018 Oct 5;165:235-250. Epub 2018 Sep 5.

Centre for Visual Information Technology, International Institute of Information Technology, Hyderabad 500032, India. Electronic address:

Background And Objective: Accurate segmentation of the intra-retinal tissue layers in Optical Coherence Tomography (OCT) images plays an important role in the diagnosis and treatment of ocular diseases such as Age-Related Macular Degeneration (AMD) and Diabetic Macular Edema (DME). The existing energy minimization based methods employ multiple, manually handcrafted cost terms and often fail in the presence of pathologies. In this work, we eliminate the need to handcraft the energy by learning it from training images in an end-to-end manner. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607173146
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.09.004DOI Listing
October 2018
2 Reads

Surgery of complex craniofacial defects: A single-step AM-based methodology.

Comput Methods Programs Biomed 2018 Oct 5;165:225-233. Epub 2018 Sep 5.

Department of Pediatric Surgery, Meyer Children's Hospital, Viale Pieraccini 24, 50141 Florence, Italy.

Background And Objective: The purpose of the present paper is to pave the road to the systematic optimization of complex craniofacial surgical intervention and to validate a design methodology for the virtual surgery and the fabrication of cranium vault custom plates. Recent advances in the field of medical imaging, image processing and additive manufacturing (AM) have led to new insights in several medical applications. The engineered combination of medical actions and 3D processing steps, foster the optimization of the intervention in terms of operative time and number of sessions needed. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183086
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.09.002DOI Listing
October 2018
3 Reads

Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.

Comput Methods Programs Biomed 2018 Oct 31;165:215-224. Epub 2018 Aug 31.

School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Republic of Korea. Electronic address:

Background And Objective: In pulmonary nodule detection, the first stage, candidate detection, aims to detect suspicious pulmonary nodules. However, detected candidates include many false positives and thus in the following stage, false positive reduction, such false positives are reliably reduced. Note that this task is challenging due to 1) the imbalance between the numbers of nodules and non-nodules and 2) the intra-class diversity of non-nodules. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183074
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.012DOI Listing
October 2018
5 Reads

An effective computer aided diagnosis model for pancreas cancer on PET/CT images.

Comput Methods Programs Biomed 2018 Oct 4;165:205-214. Epub 2018 Sep 4.

Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA.

Background and objective: Pancreas cancer is a digestive tract tumor with high malignancy, which is difficult for diagnosis and treatment at early time. To this end, this paper proposes a computer aided diagnosis (CAD) model for pancreas cancer on Positron Emission Tomography/Computed Tomography (PET/CT) images.

Methods: There are three essential steps in the proposed CAD model, including (1) pancreas segmentation, (2) feature extraction and selection, (3) classifier design, respectively. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183050
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.09.001DOI Listing
October 2018
2 Reads

Classification of glucose records from patients at diabetes risk using a combined permutation entropy algorithm.

Comput Methods Programs Biomed 2018 Oct 1;165:197-204. Epub 2018 Sep 1.

Internal Medicine Service at the University Hospital of Móstoles Río Júcar s/n, Móstoles, Madrid 28935, Spain.

Background And Objectives: The adoption in clinical practice of electronic portable blood or interstitial glucose monitors has enabled the collection, storage, and sharing of massive amounts of glucose level readings. This availability of data opened the door to the application of a multitude of mathematical methods to extract clinical information not discernible with conventional visual inspection. The objective of this study is to assess the capability of Permutation Entropy (PE) to find differences between glucose records of healthy and potentially diabetic subjects. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183020
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.018DOI Listing
October 2018
3 Reads

Tracking tumor boundary using point correspondence for adaptive radio therapy.

Comput Methods Programs Biomed 2018 Oct 22;165:187-195. Epub 2018 Aug 22.

Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada; Servier Virtual Cardiac Centre, Mazankowski Alberta Heart Institute, Edmonton, Alberta, Canada; Department of Radiology & Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada.

Background And Objective: Tracking mobile tumor regions during the treatment is a crucial part of image-guided radiation therapy because of two main reasons which negatively affect the treatment process: (1) a tiny error will lead to some healthy tissues being irradiated; and (2) some cancerous cells may survive if the beam is not accurately positioned as it may not cover the entire cancerous region. However, tracking or delineation of such a tumor region from magnetic resonance imaging (MRI) is challenging due to photometric similarities of the region of interest and surrounding area as well as the influence of motion in the organs. The purpose of this work is to develop an approach to track the center and boundary of tumor region by auto-contouring the region of interest in moving organs for radiotherapy. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607173038
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.002DOI Listing
October 2018
4 Reads

Automated recognition of cardiac arrhythmias using sparse decomposition over composite dictionary.

Comput Methods Programs Biomed 2018 Oct 22;165:175-186. Epub 2018 Aug 22.

Department of Electrical Engineering, Indian Institute of Technology Patna, Bihta 801103, India. Electronic address:

Background And Objective: Cardiovascular diseases (CVDs) are the leading cause of deaths worldwide. Due to an increase in the rate of global mortalities, biopathological signal processing and evaluation are widely used in the ambulatory situations for healthcare applications. For decades, the processing of pathological electrocardiogram (ECG) signals for arrhythmia detection has been thoroughly studied for diagnosis of various cardiovascular diseases. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183072
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.008DOI Listing
October 2018
3 Reads

A novel cumulative level difference mean based GLDM and modified ABCD features ranked using eigenvector centrality approach for four skin lesion types classification.

Comput Methods Programs Biomed 2018 Oct 24;165:163-174. Epub 2018 Aug 24.

Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt.

Background And Objective: Melanoma is one of the major death causes while basal cell carcinoma (BCC) is the utmost incident skin lesion type. At their early stages, medical experts may be confused between both types with benign nevus and pigmented benign keratoses (BKL). This inspired the current study to develop an accurate automated, user-friendly skin lesion identification system. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.08.009DOI Listing
October 2018
1 Read

BE-DTI': Ensemble framework for drug target interaction prediction using dimensionality reduction and active learning.

Comput Methods Programs Biomed 2018 Oct 22;165:151-162. Epub 2018 Aug 22.

Computer Science and Engineering Department, Thapar Institute of Engineering & Technology, Punjab, Patiala, India. Electronic address:

Background And Objective: Drug-target interaction prediction plays an intrinsic role in the drug discovery process. Prediction of novel drugs and targets helps in identifying optimal drug therapies for various stringent diseases. Computational prediction of drug-target interactions can help to identify potential drug-target pairs and speed-up the process of drug repositioning. Read More

View Article

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmpb.2018.08.011DOI Listing
October 2018

A hybrid data mining model for diagnosis of patients with clinical suspicion of dementia.

Comput Methods Programs Biomed 2018 Oct 24;165:139-149. Epub 2018 Aug 24.

Computer Modelling Department, State of Rio de Janeiro University, Rua Bonfim, 25 - Vila Amélia - CEP 28625-570 - Nova Friburgo, Rio de Janeiro, Brazil; Veiga de Almeida University, Rua Ibituruna, 108 - Maracanã - CEP 20271-020, Rio de Janeiro, Brazil. Electronic address:

Background And Objective: Given the phenomenon of aging population, dementias arise as a complex health problem throughout the world. Several methods of machine learning have been applied to the task of predicting dementias. Given its diagnostic complexity, the great challenge lies in distinguishing patients with some type of dementia from healthy people. Read More

View Article

Download full-text PDF

Source
https://linkinghub.elsevier.com/retrieve/pii/S01692607183075
Publisher Site
http://dx.doi.org/10.1016/j.cmpb.2018.08.016DOI Listing
October 2018
3 Reads