1,332 results match your criteria Artificial Intelligence in Medicine [Journal]


MRI denoising by NeighShrink based on chi-square unbiased risk estimation.

Artif Intell Med 2019 Jan 31. Epub 2019 Jan 31.

College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua, China.

NeighShrink is an efficient image denoising algorithm for the reduction of additive white Gaussian noise. However, it does not perform well in terms of Rician noise removal for MRI (Magnetic Resonance Imaging). Allowing for the characteristics of squared-magnitude MR (Magnetic Resonance) images, which follow a non-central chi-square distribution, the CURE (Chi-Square Unbiased Risk Estimation) is used to determine an optimal threshold for NeighShrink. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.12.001DOI Listing
January 2019
1 Read

A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity.

Artif Intell Med 2019 Jan 22. Epub 2019 Jan 22.

Radboud University Nijmegen Medical Centre, The Netherlands. Electronic address:

Background: Recently, mobile devices, such as smartphones, have been introduced into healthcare research to substitute paper diaries as data-collection tools in the home environment. Such devices support collecting patient data at different time points over a long period, resulting in clinical time-series data with high temporal complexity, such as time irregularities. Analysis of such time series poses new challenges for machine-learning techniques. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657173049
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http://dx.doi.org/10.1016/j.artmed.2018.10.002DOI Listing
January 2019
5 Reads

Project INSIDE: towards autonomous semi-unstructured human-robot social interaction in autism therapy.

Artif Intell Med 2018 Dec 28. Epub 2018 Dec 28.

Instituto Superior Técnico, University of Lisbon, Portugal.

This paper describes the INSIDE system, a networked robot system designed to allow the use of mobile robots as active players in the therapy of children with autism spectrum disorders (ASD). While a significant volume of work has explored the impact of robots in ASD therapy, most such work comprises remotely operated robots and/or well-structured interaction dynamics. In contrast, the INSIDE system allows for complex, semi-unstructured interaction in ASD therapy while featuring a fully autonomous robot. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.12.003DOI Listing
December 2018
1 Read
2.019 Impact Factor

A novel dynamical approach in continuous cuffless blood pressure estimation based on ECG and PPG signals.

Artif Intell Med 2018 Dec 23. Epub 2018 Dec 23.

Biomedical Engineering Department, Hamedan University of Technology, Hamedan, 6516913733, Iran. Electronic address:

Continuous cuffless blood pressure (BP) monitoring has attracted much interest in finding the ideal treatment of diseases and the prevention of premature death. This paper presents a novel dynamical method, based on pulse transit time (PTT) and photoplethysmogram intensity ratio (PIR), for the continuous cuffless BP estimation. By taking the advantages of both the modeling and the prediction approaches, the proposed framework effectively estimates diastolic BP (DBP), mean BP (BP), and systolic BP (SBP). Read More

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http://dx.doi.org/10.1016/j.artmed.2018.12.005DOI Listing
December 2018
1 Read

BDI personal medical assistant agents: The case of trauma tracking and alerting.

Artif Intell Med 2018 Dec 19. Epub 2018 Dec 19.

Intensive Care Unit/Trauma Center, M. Bufalini Hospital, Cesena, Italy. Electronic address:

Personal assistant agents can have an important role in healthcare as a smart technology to support physicians in their daily work, helping to tackle the increasing complexity of their task environment. In this paper we present and discuss a personal medical assistant agent technology for trauma documentation and management, based on the Belief-Desire-Intention (BDI) architecture. The purpose of the personal assistant agent is twofold: to assist the Trauma Team in doing precision tracking during a trauma resuscitation, so as to (automatically) produce an accurate documentation of the trauma, and to generate alerts at real-time, to be eventually displayed either on smart-glasses or room-display. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.12.002DOI Listing
December 2018
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Fuzzy logic based approaches for gene regulatory network inference.

Authors:
Khalid Raza

Artif Intell Med 2018 Dec 17. Epub 2018 Dec 17.

Department of Computer Science, Jamia Millia Islamia, New Delhi, India. Electronic address:

The rapid advancements in high-throughput techniques have fueled large-scale production of biological data at very affordable costs. Some of these techniques are microarrays and next-generation sequencing that provide genome level insight of living cells. As a result, the size of most of the biological databases, such as NCBI-GEO, NCBI-SRA, etc. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.12.004DOI Listing
December 2018
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CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm.

Artif Intell Med 2018 Dec 14. Epub 2018 Dec 14.

Faculty of Computers and Information, Cairo University, Cairo, Egypt; Scientific Research Group in Egypt (SRGE), Egypt(1).

Liver tumor segmentation from computed tomography (CT) images is a critical and challenging task. Due to the fuzziness in the liver pixel range, the neighboring organs of the liver with the same intensity, high noise and large variance of tumors. The segmentation process is necessary for the detection, identification, and measurement of objects in CT images. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.11.007DOI Listing
December 2018
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Optimal testing policies for diagnosing patients with intermediary probability of disease.

Artif Intell Med 2018 Dec 5. Epub 2018 Dec 5.

Instituto Nacional de Cardiologia, Rua das Laranjeiras 374, Laranjeiras, Rio de Janeiro, RJ, 22.240-006, Brazil. Electronic address:

This paper proposes a stochastic shortest path approach to find an optimal sequence of tests to confirm or discard a disease, for any prescribed optimality criterion. The idea is to select the best sequence in which to apply a series of available tests, with a view at reaching a diagnosis with minimum expenditure of resources. The proposed approach derives an optimal policy whereby the decision maker is provided with a test strategy for each a priori probability of disease, aiming to reach posterior probabilities that warrant either immediate treatment or a not-ill diagnosis. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.11.005DOI Listing
December 2018
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Arden Syntax: Then, now, and in the future.

Artif Intell Med 2018 Nov 25;92:1-6. Epub 2018 Oct 25.

Department of Medicine & Clinical and Translational Science Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA; Center for Biomedical Informatics, Charles Drew University, 1748 E 118th Street, LSRNE N238, Los Angeles, CA 90059, USA.

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http://dx.doi.org/10.1016/j.artmed.2018.09.001DOI Listing
November 2018
2 Reads

An efficient and fast computer-aided method for fully automated diagnosis of meniscal tears from magnetic resonance images.

Artif Intell Med 2018 Dec 4. Epub 2018 Dec 4.

Computer Engineering Department, Yıldız Technical University, İstanbul, Turkey. Electronic address:

Menisci are structures that directly affect movement, so early detection of meniscus tears also helps to prevent progressive knee disorders such as osteoarthritis. Manual segmentation of the menisci and diagnosis of the meniscal tear is a costly process in terms of time and effort for a radiologist. The aim of this study is to automatically determine the location and the type of meniscal tears that are important in the diagnosis and effective treatment of this problem. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.11.008DOI Listing
December 2018
2 Reads

A computer-aided diagnosis system for HEp-2 fluorescence intensity classification.

Artif Intell Med 2018 Nov 28. Epub 2018 Nov 28.

Unit of Computer Systems and Bioinformatics, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy. Electronic address:

Background And Objective: The indirect immunofluorescence (IIF) on HEp-2 cells is the recommended technique for the detection of antinuclear antibodies. However, it is burdened by some limitations, as it is time consuming and subjective, and it requires trained personnel. In other fields the adoption of deep neural networks has provided an effective high-level abstraction of the raw data, resulting in the ability to automatically generate optimized high-level features. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.11.002DOI Listing
November 2018
1 Read

Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome.

Artif Intell Med 2018 Nov 28. Epub 2018 Nov 28.

Univ Rennes, CHU Rennes, Inserm, LTSI UMR 1099, F-35000 Rennes, France.

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657183044
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http://dx.doi.org/10.1016/j.artmed.2018.11.006DOI Listing
November 2018
3 Reads

Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.

Artif Intell Med 2018 Nov 23. Epub 2018 Nov 23.

Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.

This paper explores cutting-edge deep learning methods for information extraction from medical imaging free text reports at a multi-institutional scale and compares them to the state-of-the-art domain-specific rule-based system - PEFinder and traditional machine learning methods - SVM and Adaboost. We proposed two distinct deep learning models - (i) CNN Word - Glove, and (ii) Domain phrase attention-based hierarchical recurrent neural network (DPA-HNN), for synthesizing information on pulmonary emboli (PE) from over 7370 clinical thoracic computed tomography (CT) free-text radiology reports collected from four major healthcare centers. Our proposed DPA-HNN model encodes domain-dependent phrases into an attention mechanism and represents a radiology report through a hierarchical RNN structure composed of word-level, sentence-level and document-level representations. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657173062
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http://dx.doi.org/10.1016/j.artmed.2018.11.004DOI Listing
November 2018
13 Reads

Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning.

Artif Intell Med 2018 Nov 22. Epub 2018 Nov 22.

Hospital San Agustín, Linares, Spain.

The conciliation of multiple single-disease guidelines for comorbid patients entails solving potential clinical interactions, discovering synergies in the diagnosis and the recommendations, and managing clinical equipoise situations. Personalized conciliation of multiple guidelines considering additionally patient preferences brings some further difficulties. Recently, several works have explored distinct techniques to come up with an automated process for the conciliation of clinical guidelines for comorbid patients but very little attention has been put in integrating the patient preferences into this process. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.11.003DOI Listing
November 2018
2 Reads

Diabetic retinopathy techniques in retinal images: A review.

Artif Intell Med 2018 Nov 15. Epub 2018 Nov 15.

Military College of Signals, Department of Information Security, National University of Science and Technology, Rawalpindi, Pakistan. Electronic address:

The diabetic retinopathy is the main reason of vision loss in people. Medical experts recognize some clinical, geometrical and haemodynamic features of diabetic retinopathy. These features include the blood vessel area, exudates, microaneurysm, hemorrhages and neovascularization, etc. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.10.009DOI Listing
November 2018
1 Read

Neural network modelling of soft tissue deformation for surgical simulation.

Artif Intell Med 2018 Nov 13. Epub 2018 Nov 13.

Department of Mechanical Engineering, University of Melbourne, Parkville, VIC, 3010, Australia.

This paper presents a new neural network methodology for modelling of soft tissue deformation for surgical simulation. The proposed methodology formulates soft tissue deformation and its dynamics as the neural propagation and dynamics of cellular neural networks for real-time, realistic, and stable simulation of soft tissue deformation. It develops two cellular neural network models; based on the bioelectric propagation of biological tissues and principles of continuum mechanics, one cellular neural network model is developed for propagation and distribution of mechanical load in soft tissues; based on non-rigid mechanics of motion in continuum mechanics, the other cellular neural network model is developed for governing model dynamics of soft tissue deformation. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657173019
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http://dx.doi.org/10.1016/j.artmed.2018.11.001DOI Listing
November 2018
11 Reads

Indexing the Event Calculus: Towards practical human-readable Personal Health Systems.

Artif Intell Med 2018 Nov 12. Epub 2018 Nov 12.

Open University of the Netherlands, Heerlen, The Netherlands; BISS Institute, Heerlen, The Netherlands. Electronic address:

Personal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases. In general, a patient affected by a chronic disease can generate large amounts of events: for example, in Type 1 Diabetic patients generate several glucose events per day, ranging from at least 6 events per day (under normal monitoring) to 288 per day when wearing a continuous glucose monitor (CGM) that samples the blood every 5 minutes for several days. Just by itself, without considering other physiological parameters, it would be impossible for medical doctors to individually and accurately follow every patient, highlighting the need of simple approaches towards querying physiological time series. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.10.003DOI Listing
November 2018
10 Reads

Computational methods for Gene Regulatory Networks reconstruction and analysis: A review.

Artif Intell Med 2018 Nov 9. Epub 2018 Nov 9.

Division of Computer Science, Pablo de Olavide University, ES-41013 Seville, Spain. Electronic address:

In the recent years, the vast amount of genetic information generated by new-generation approaches, have led to the need of new data handling methods. The integrative analysis of diverse-nature gene information could provide a much-sought overview to study complex biological systems and processes. In this sense, Gene Regulatory Networks (GRN) arise as an increasingly-promising tool for the modelling and analysis of biological processes. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.10.006DOI Listing
November 2018
1 Read

Segmentation of breast MR images using a generalised 2D mathematical model with inflation and deflation forces of active contours.

Artif Intell Med 2018 Nov 9. Epub 2018 Nov 9.

School of Health Sciences, Ulster University, Newtownabbey, Northern Ireland BT37 0QB, United Kingdom.

In medical computer aided diagnosis systems, image segmentation is one of the major pre-processing steps used to ensure only the region of interest, such as the breast region, will be processed in subsequent steps. Nevertheless, breast segmentation is a difficult task due to low contrast and inhomogeneity, especially when estimating the chest wall in magnetic resonance (MR) images. In fact, the chest wall comprises fat, skin, muscles, and the thoracic skeleton, which can misguide automatic methods when attempting to estimate its location. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.10.007DOI Listing
November 2018
12 Reads

Computational normalization of H&E-stained histological images: Progress, challenges and future potential.

Artif Intell Med 2018 Nov 9. Epub 2018 Nov 9.

Center of Mathematics, Computing and Cognition, Federal University of ABC, Av. dos Estados, 5001, 09210-580, Santo André, São Paulo, Brazil; Faculty of Computer Science, Federal University of Uberlândia, Av. João Naves de Ávila, 2121, 38400-902, Uberlândia, Minas Gerais, Brazil. Electronic address:

Different types of cancer can be diagnosed with the analysis of histological samples stained with hematoxylin-eosin (H&E). Through this stain, it is possible to identify the architecture of tissue components and analyze cellular morphological aspects that are essential for cancer diagnosis. However, preparation and digitization of histological samples can lead to color variations that influence the performance of segmentation and classification algorithms in histological image analysis systems. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.10.004DOI Listing
November 2018
1 Read

Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks.

Artif Intell Med 2018 Nov 9. Epub 2018 Nov 9.

Ghent University - imec, IDLab, Department of Information Technology, Technologiepark 15, B-9052, Ghent, Belgium. Electronic address:

Introduction: Blood cultures are often performed in the intensive care unit (ICU) to detect bloodstream infections and identify pathogen type, further guiding treatment. Early detection is essential, as a bloodstream infection can give cause to sepsis, a severe immune response associated with an increased risk of organ failure and death.

Problem Statement: The early clinical detection of a bloodstream infection is challenging but rapid targeted treatment, within the first place antimicrobials, substantially increases survival chances. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.10.008DOI Listing
November 2018
3 Reads

Early anomaly detection in smart home: A causal association rule-based approach.

Artif Intell Med 2018 Sep 29;91:57-71. Epub 2018 Jun 29.

CNRS Paris Saclay, Telecom SudParis, SAMOVAR, France. Electronic address:

As the world's population grows older, an increasing number of people are facing health issues. For the elderly, living alone can be difficult and dangerous. Consequently, smart homes are becoming increasingly popular. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.06.001DOI Listing
September 2018
12 Reads

Preface: AIME 2017.

Artif Intell Med 2018 Sep;91:1-2

University of Pavia, Pavia, Italy.

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http://dx.doi.org/10.1016/j.artmed.2018.10.005DOI Listing
September 2018
1 Read

Towards automatic encoding of medical procedures using convolutional neural networks and autoencoders.

Artif Intell Med 2019 Jan 29;93:29-42. Epub 2018 Oct 29.

Bern University of Applied Sciences, Medical Informatics, Biel, Switzerland.

Classification systems such as ICD-10 for diagnoses or the Swiss Operation Classification System (CHOP) for procedure classification in the clinical treatment are essential for clinical management and information exchange. Traditionally, classification codes are assigned manually or by systems that rely upon concept-based or rule-based classification methods. Such methods can reach their limit easily due to the restricted coverage of handcrafted rules and of the vocabulary in underlying terminological systems. Read More

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January 2019
7 Reads

On predicting epithelial mesenchymal transition by integrating RNA-binding proteins and correlation data via L-regularization method.

Artif Intell Med 2018 Oct 20. Epub 2018 Oct 20.

Department of Mathematics, Hong Kong Baptist University, Hong Kong. Electronic address:

Identifying tumor metastasis signatures from gene expression data at the whole genome level remains an arduous challenge, particularly so when the number of genes is huge and the number of experimental samples is small. We focus on the prediction of the epithelial-mesenchymal transition (EMT), which is an underlying mechanism of tumor metastasis, here, rather than on tumor metastasis itself, to avoid confounding effects of uncertainties derived from various factors. We apply an extended LASSO model, L-regularization model, as a feature selector, to identify significant RNA-binding proteins (RBPs) that contribute to regulating the EMT. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.09.005DOI Listing
October 2018
1 Read
2.020 Impact Factor

Towards a modular decision support system for radiomics: A case study on rectal cancer.

Artif Intell Med 2018 Oct 3. Epub 2018 Oct 3.

Polo Scienze Oncologiche ed Ematologiche, Fondazione Policlinico Universitario Agostino Gemelli, Largo A. Gemelli, 8, 00168 Rome, Italy.

Following the personalized medicine paradigm, there is a growing interest in medical agents capable of predicting the effect of therapies on patients, by exploiting the amount of data that is now available for each patient. In disciplines like oncology, where images and scans are available, the exploitation of medical images can provide an additional source of potentially useful information. The study and analysis of features extracted by medical images, exploited for predictive purposes, is termed radiomics. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.09.003DOI Listing
October 2018
3 Reads

Predicting hospital associated disability from imbalanced data using supervised learning.

Artif Intell Med 2018 Oct 3. Epub 2018 Oct 3.

University of Jyvaskyla, Faculty of Information Technology, P.O. Box 35, FI-40014, University of Jyvaskyla, Finland.

Hospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to such adverse effects is an active area of medical research. The purpose of the current paper is to show the potential of artificial intelligence in the form of machine learning to complement the existing medical research. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657183030
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http://dx.doi.org/10.1016/j.artmed.2018.09.004DOI Listing
October 2018
7 Reads

A methodology for customizing clinical tests for esophageal cancer based on patient preferences.

Artif Intell Med 2018 Sep 29. Epub 2018 Sep 29.

Indian Institute of Technology (IIT), Kharagpur, India.

Background: Clinical tests for diagnosis of any disease may be expensive, uncomfortable, time consuming and can have side effects e.g. barium swallow test for esophageal cancer. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657163054
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http://dx.doi.org/10.1016/j.artmed.2018.08.001DOI Listing
September 2018
9 Reads

Pathological image compression for big data image analysis: Application to hotspot detection in breast cancer.

Artif Intell Med 2018 Sep 25. Epub 2018 Sep 25.

University of Arizona, Tucson, AZ, USA.

In this paper, we propose a pathological image compression framework to address the needs of Big Data image analysis in digital pathology. Big Data image analytics require analysis of large databases of high-resolution images using distributed storage and computing resources along with transmission of large amounts of data between the storage and computing nodes that can create a major processing bottleneck. The proposed image compression framework is based on the JPEG2000 Interactive Protocol and aims to minimize the amount of data transfer between the storage and computing nodes as well as to considerably reduce the computational demands of the decompression engine. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.09.002DOI Listing
September 2018
2 Reads

Predicting ICU readmission using grouped physiological and medication trends.

Artif Intell Med 2018 Sep 10. Epub 2018 Sep 10.

Department of Preventive Medicine, Northwestern University, Chicago, IL, USA. Electronic address:

Background: Patients who are readmitted to an intensive care unit (ICU) usually have a high risk of mortality and an increased length of stay. ICU readmission risk prediction may help physicians to re-evaluate the patient's physical conditions before patients are discharged and avoid preventable readmissions. ICU readmission prediction models are often built based on physiological variables. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.08.004DOI Listing
September 2018
13 Reads

A survey on computer-assisted Parkinson's Disease diagnosis.

Artif Intell Med 2018 Sep 7. Epub 2018 Sep 7.

São Paulo State University, School of Sciences, Bauru, Brazil.

Background And Objective: In this work, we present a systematic review concerning the recent enabling technologies as a tool to the diagnosis, treatment and better quality of life of patients diagnosed with Parkinson's Disease (PD), as well as an analysis of future trends on new approaches to this end.

Methods: In this review, we compile a number of works published at some well-established databases, such as Science Direct, IEEEXplore, PubMed, Plos One, Multidisciplinary Digital Publishing Institute (MDPI), Association for Computing Machinery (ACM), Springer and Hindawi Publishing Corporation. Each selected work has been carefully analyzed in order to identify its objective, methodology and results. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.08.007DOI Listing
September 2018
2 Reads

Association measures for estimating semantic similarity and relatedness between biomedical concepts.

Artif Intell Med 2019 Jan 7;93:1-10. Epub 2018 Sep 7.

Virginia Commonwealth University, Richmond, VA, United States.

Association measures quantify the observed likelihood a term pair co-occurs versus their predicted co-occurrence together if by chance. This is based both on the terms' individual occurrence frequencies, and their mutual co-occurrence frequencies. One application of association scores is estimating semantic relatedness, which is critical for many natural language processing applications, such as clustering of biomedical and clinical documents and the development of biomedical terminologies and ontololgies. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.08.006DOI Listing
January 2019
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Evaluation of the Tinetti score and fall risk assessment via accelerometry-based movement analysis.

Artif Intell Med 2018 Sep 5. Epub 2018 Sep 5.

Dipartimento di Informatica, Università degli Studi di Milano, Crema (CR) 26013, Italy. Electronic address:

Gait and balance disorders are among the main predisposing factors of falls in elderly. Clinical scales are widely employed to assess the risk of falling, but they require trained personnel. We investigate the use of objective measures obtained from a wearable accelerometer to evaluate the fall risk, determined by the Tinetti clinical scale. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657173039
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http://dx.doi.org/10.1016/j.artmed.2018.08.005DOI Listing
September 2018
14 Reads

Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review.

Artif Intell Med 2018 Sep 5. Epub 2018 Sep 5.

Computer Vision and Robotics Institute, Dept. of Computer Architecture and Technology, University of Girona, Ed. P-IV, Av. Lluis Santaló s/n, 17003 Girona, Spain. Electronic address:

In recent years, deep convolutional neural networks (CNNs) have shown record-shattering performance in a variety of computer vision problems, such as visual object recognition, detection and segmentation. These methods have also been utilised in medical image analysis domain for lesion segmentation, anatomical segmentation and classification. We present an extensive literature review of CNN techniques applied in brain magnetic resonance imaging (MRI) analysis, focusing on the architectures, pre-processing, data-preparation and post-processing strategies available in these works. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.08.008DOI Listing
September 2018
2 Reads

An architecture of open-source tools to combine textual information extraction, faceted search and information visualisation.

Artif Intell Med 2019 Jan 5;93:13-28. Epub 2018 Sep 5.

German Research Center for Artificial Intelligence, DFKI, 66123 Saarbrücken, Germany.

This article presents our steps to integrate complex and partly unstructured medical data into a clinical research database with subsequent decision support. Our main application is an integrated faceted search tool, accompanied by the visualisation of results of automatic information extraction from textual documents. We describe the details of our technical architecture (open-source tools), to be replicated at other universities, research institutes, or hospitals. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.08.003DOI Listing
January 2019
1 Read

Surgical motion analysis using discriminative interpretable patterns.

Artif Intell Med 2018 Sep 30;91:3-11. Epub 2018 Aug 30.

Univ Rennes, Inserm, LTSI - UMR_S 1099, F35000 Rennes, France. Electronic address:

Objective: The analysis of surgical motion has received a growing interest with the development of devices allowing their automatic capture. In this context, the use of advanced surgical training systems makes an automated assessment of surgical trainee possible. Automatic and quantitative evaluation of surgical skills is a very important step in improving surgical patient care. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.08.002DOI Listing
September 2018
10 Reads

Mining heterogeneous networks with topological features constructed from patient-contributed content for pharmacovigilance.

Artif Intell Med 2018 Aug 6;90:42-52. Epub 2018 Aug 6.

College of Computing and Informatics, Drexel University, United States.

Drug safety, also called pharmacovigilance, represents a serious health problem all over the world. Adverse drug reactions (ADRs) and drug-drug interactions (DDIs) are two important issues in pharmacovigilance, and how to detect drug safety signals has drawn many researchers' attention and efforts. Currently, methods proposed for ADR and DDI detection are mainly based on traditional data sources such as spontaneous reporting data, electronic health records, pharmaceutical databases, and biomedical literature. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.07.002DOI Listing
August 2018
3 Reads

Recent advances in extracting and processing rich semantics from medical texts.

Artif Intell Med 2019 Jan 3;93:11-12. Epub 2018 Aug 3.

Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

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http://dx.doi.org/10.1016/j.artmed.2018.07.004DOI Listing
January 2019
2 Reads

Causality assessment of adverse drug reaction reports using an expert-defined Bayesian network.

Artif Intell Med 2018 Sep 2;91:12-22. Epub 2018 Aug 2.

CINTESIS - Centre for Health Technology and Services Research, Rua Dr. Plácido Costa, 4200-450 Porto, Portugal; UFN - Northern Pharmacovigilance Centre (INFARMED), Rua Dr. Plácido Costa, 4200-450 Porto, Portugal.

In pharmacovigilance, reported cases are considered suspected adverse drug reactions (ADR). Health authorities have thus adopted structured causality assessment methods, allowing the evaluation of the likelihood that a drug was the causal agent of an adverse reaction. The aim of this work was to develop and validate a new causality assessment support system used in a regional pharmacovigilance centre. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S09333657173061
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http://dx.doi.org/10.1016/j.artmed.2018.07.005DOI Listing
September 2018
16 Reads

Diagnosis labeling with disease-specific characteristics mining.

Artif Intell Med 2018 Aug 31;90:25-33. Epub 2018 Jul 31.

School of Information Science and Technology, Northwest University, Xian 710127, PR China. Electronic address:

Data analysis and management of huge volumes of medical data have attracted enormous attention, since discovering knowledge from the data can benefit both caregivers and patients. In this paper, we focus on learning disease labels from medical data of patients in Intensive Care Units (ICU). Specifically, we extract features from two main sources, medical charts and notes. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.06.006DOI Listing
August 2018
7 Reads

Dependence between cognitive impairment and metabolic syndrome applied to a Brazilian elderly dataset.

Artif Intell Med 2018 Aug 31;90:53-60. Epub 2018 Jul 31.

Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, Brazil.

Globally, the proportion of elderly individuals in the population has increased substantially in the last few decades. However, the risk factors that should be managed in advance to ensure a natural process of mental decline due to aging remain unknown. In this study, a dataset consisting of a Brazilian elderly sample was modelled using a Bayesian Network (BN) approach to uncover connections between cognitive performance measures and potential influence factors. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.07.003DOI Listing
August 2018
66 Reads
2.020 Impact Factor

Abdominal, multi-organ, auto-contouring method for online adaptive magnetic resonance guided radiotherapy: An intelligent, multi-level fusion approach.

Artif Intell Med 2018 Aug 24;90:34-41. Epub 2018 Jul 24.

Department of Radiology, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Case Center for Imaging Research, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, OH, USA; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA. Electronic address:

Background: Manual contouring remains the most laborious task in radiation therapy planning and is a major barrier to implementing routine Magnetic Resonance Imaging (MRI) Guided Adaptive Radiation Therapy (MR-ART). To address this, we propose a new artificial intelligence-based, auto-contouring method for abdominal MR-ART modeled after human brain cognition for manual contouring.

Methods/materials: Our algorithm is based on two types of information flow, i. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.07.001DOI Listing
August 2018
5 Reads

Decision support system for detection of hypertensive retinopathy using arteriovenous ratio.

Artif Intell Med 2018 Aug 2;90:15-24. Epub 2018 Jul 2.

Department of Computer & Software Engineering, College of E&ME, National University of Sciences and Technology, Islamabad, Pakistan. Electronic address:

Hypertensive Retinopathy (HR) caused by hypertension is a retinal disease which may leads to vision loss and blindness. Computer aided diagnostic systems for various diseases are being used in clinics but there is a need to develop an automated system that detects and grades HR disease. In this paper, an automated system is presented that detects and grades HR disease using Arteriovenous Ratio (AVR). Read More

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http://dx.doi.org/10.1016/j.artmed.2018.06.004DOI Listing
August 2018
9 Reads
2.019 Impact Factor

Change-point detection method for clinical decision support system rule monitoring.

Artif Intell Med 2018 Sep 3;91:49-56. Epub 2018 Jul 3.

Department of Computer Science, University of Pittsburgh, USA. Electronic address:

A clinical decision support system (CDSS) helps clinicians to manage patients, but malfunctions of its components or other systems on which it depends may affect its intended functions. Monitoring the system and detecting changes in its behavior that may indicate the malfunction can help to avoid any potential costs associated with its improper operation. In this paper, we investigate the problem of detecting changes in the CDSS operation, in particular its monitoring and alerting subsystem, by monitoring its rule firing counts. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.06.003DOI Listing
September 2018
2 Reads

Process models of interrelated speech intentions from online health-related conversations.

Artif Intell Med 2018 Sep 18;91:23-38. Epub 2018 Jul 18.

University of Ljubljana, Večna pot 113, 1000 Ljubljana, Slovenia.

Being related to the adoption of new beliefs, attitudes and, ultimately, behaviors, analyzing online communication is of utmost importance for medicine. Multiple health care, academic communities, such as information seeking and dissemination and persuasive technologies, acknowledge this need. However, in order to obtain understanding, a relevant way to model online communication for the study of behavior is required. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.06.007DOI Listing
September 2018
4 Reads

Detecting mental fatigue from eye-tracking data gathered while watching video: Evaluation in younger and older adults.

Artif Intell Med 2018 Sep 17;91:39-48. Epub 2018 Jul 17.

IBM Research - Tokyo, 19-21, Nihonbashi, Hakozaki-cho, Chuo-ku, Tokyo 103-8510, Japan.

Health monitoring technology in everyday situations is expected to improve quality of life and support aging populations. Mental fatigue among health indicators of individuals has become important due to its association with cognitive performance and health outcomes, especially in older adults. Previous models using eye-tracking measures allow inference of fatigue during cognitive tasks, such as driving, but they require us to engage in specific cognitive tasks. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.06.005DOI Listing
September 2018
6 Reads

A review of statistical and machine learning methods for modeling cancer risk using structured clinical data.

Artif Intell Med 2018 Aug 14;90:1-14. Epub 2018 Jul 14.

Florida Atlantic University, United States. Electronic address:

Advancements are constantly being made in oncology, improving prevention and treatment of cancers. To help reduce the impact and deadliness of cancers, they must be detected early. Additionally, there is a risk of cancers recurring after potentially curative treatments are performed. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.06.002DOI Listing
August 2018
3 Reads

Modeling the connections of brain regions in children with autism using cellular neural networks and electroencephalography analysis.

Artif Intell Med 2018 Jul 11;89:40-50. Epub 2018 Jul 11.

Department of Control Engineering, K. N. Toosi University of Technology, Tehran, Iran.

The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). Read More

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http://dx.doi.org/10.1016/j.artmed.2018.05.003DOI Listing
July 2018
9 Reads

A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis.

Artif Intell Med 2018 Jul 19;89:34-39. Epub 2018 Jun 19.

Department of Information and Computing Science, China Jiliang University, Hangzhou 310018, PR China.

The intuitionistic fuzzy set, as a generation of fuzzy set, can express and process uncertainty much better. Distance measures between intuitionistic fuzzy sets are used to indicate the difference degree between the information carried by intuitionistic fuzzy sets. Although some distance measures have been proposed in previous studies, they can not satisfy the axioms of distance measure, or exist counter-intuitive cases. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.05.002DOI Listing
July 2018
3 Reads

Automatic classification of radiological reports for clinical care.

Artif Intell Med 2018 Sep 7;91:72-81. Epub 2018 Jun 7.

Spedali Civili di Brescia, Italy.

Radiological reporting generates a large amount of free-text clinical narratives, a potentially valuable source of information for improving clinical care and supporting research. The use of automatic techniques to analyze such reports is necessary to make their content effectively available to radiologists in an aggregated form. In this paper we focus on the classification of chest computed tomography reports according to a classification schema proposed for this task by radiologists of the Italian hospital ASST Spedali Civili di Brescia. Read More

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http://dx.doi.org/10.1016/j.artmed.2018.05.006DOI Listing
September 2018
4 Reads