Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach
This study aims to develop a predictive model based on machine learning algorithms to identify patients at high risk of readmission.MethodsA retrospective dataset (2001–2017) including 16,902 patients admitted into a large inpatient rehabilitation facility in North Carolina was collected in 2017. Three types of machine learning models with different predictors were compared in 2018. The model with the highest c-statistic was selected as the best model and further tested by using five sets of training and validation data with different split time. The optimum threshold for classification was identified.ResultsThe logi...
Source: Journal of Biomedical Informatics - September 18, 2018 Category: Information Technology Source Type: research

A Comparison of Word Embeddings for the Biomedical Natural Language Processing
Conclusion Based on the evaluation results, we can draw the following conclusions. First, the word embeddings trained on EHR and MedLit can capture the semantics of medical terms better and find semantically relevant medical terms closer to human experts’ judgments than those trained on GloVe and Google News. Second, there does not exist a consistent global ranking of word embeddings for all downstream biomedical NLP applications. However, adding word embeddings as extra features will improve results on most downstream tasks. Finally, the word embeddings trained on biomedical domain corpora do not necessarily have be...
Source: Journal of Biomedical Informatics - September 12, 2018 Category: Information Technology Source Type: research

Corrigendum to “Symptom severity prediction from neuropsychiatric clinical records: Overview of 2016 CEGS N-GRID shared tasks Track 2” [J Biomed Inform. 2017 Nov;75S:S62–S70]
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): Michele Filannino, Amber Stubbs, Özlem Uzuner (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 11, 2018 Category: Information Technology Source Type: research

Cover 1/Spine
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 11, 2018 Category: Information Technology Source Type: research

Cover 2: Editorial Board
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 11, 2018 Category: Information Technology Source Type: research

fmi-ii: Table of Contents
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 11, 2018 Category: Information Technology Source Type: research

Identifying Health Information Technology Related Safety Event Reports from Patient Safety Event Report Databases
ConclusionThe feature-constraint model provides a method to identify HIT-related patient safety hazards using a method that is applicable across healthcare systems with variability in their PSE report structures.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 11, 2018 Category: Information Technology Source Type: research

Supporting biomedical ontology evolution by identifying outdated concepts and the required type of change
Publication date: Available online 8 September 2018Source: Journal of Biomedical InformaticsAuthor(s): Silvio Domingos Cardoso, Cédric Pruski, Marcos Da SilveiraAbstractThe consistent evolution of ontologies is a major challenge for systems using semantically enriched data, for example, for annotating, indexing, or reasoning. The biomedical domain is a typical example where ontologies, expressed with different formalisms, have been used for a long time and whose dynamic nature requires the regular revision of underlying systems. However, the automatic identification of outdated concepts and proposition of revision a...
Source: Journal of Biomedical Informatics - September 9, 2018 Category: Information Technology Source Type: research

Networked medical data sharing on secure medium – A web publishing mode for DICOM viewer with three layer authentication
Publication date: October 2018Source: Journal of Biomedical Informatics, Volume 86Author(s): Sridevi Arumugham, Sundararaman Rajagopalan, John Bosco Balaguru Rayappan, Rengarajan AmirtharajanAbstractGrowing demand for e-healthcare across the globe has raised concerns towards the secure and authentication enhanced medical image sharing. One of the services offered by health informatics in hospitals include an user interface through the Local Area Network (LAN) for enabling storage and access of medical records. In this paper, a security enhanced DICOM image sharing over a LAN addressing confidentiality, integrity and authen...
Source: Journal of Biomedical Informatics - September 9, 2018 Category: Information Technology Source Type: research

Quality Assurance of Biomedical Terminologies and Ontologies
Publication date: Available online 8 September 2018Source: Journal of Biomedical InformaticsAuthor(s): James Geller, Yehoshua Perl, Licong Cui, GQ Zhang (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 8, 2018 Category: Information Technology Source Type: research

An Evaluation of Clinical Order Patterns Machine-Learned from Clinician Cohorts Stratified by Patient Mortality Outcomes
Publication date: Available online 7 September 2018Source: Journal of Biomedical InformaticsAuthor(s): Jason K. Wang, Jason Hom, Santhosh Balasubramanian, Alejandro Schuler, Nigam H. Shah, Mary K. Goldstein, Michael T.M. Baiocchi, Jonathan H. ChenAbstractObjectiveEvaluate the quality of clinical order practice patterns machine-learned from clinician cohorts stratified by patient mortality outcomes.Materials and MethodsInpatient electronic health records from 2010-2013 were extracted from a tertiary academic hospital. Clinicians (n=1,822) were stratified into low-mortality (21.8%, n=397) and high-mortality (6.0%, n=110) ext...
Source: Journal of Biomedical Informatics - September 7, 2018 Category: Information Technology Source Type: research

The use of model constructs to design collaborative health information technologies: a case study to support child development
ConclusionsDeductive analysis considering model constructs provides a useful approach to designing collaborative HIT systems, allowing designers to consider both empirical user data and existing knowledge from the literature. This method has the potential to improve designs for collaborative HIT systems.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 7, 2018 Category: Information Technology Source Type: research

Identification of target gene and prognostic evaluation for lung adenocarcinoma using gene expression meta-analysis, network analysis and neural network algorithms
ConclusionOur study has identified novel candidate biomarkers, pathways, transcription factors (TFs), and kinases associated with NSCLC prognosis, as well as drug candidates, which may assist treatment strategy for NSCLC patients.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - September 7, 2018 Category: Information Technology Source Type: research

Mixed Effect Machine Learning: a framework for predicting longitudinal change in hemoglobin A1c
In this study, we formulate an analytic framework, which integrates the random-effects structure of GLMM into non-linear machine learning models capable of exploiting temporal heterogeneous effects, sparse and varying-length patient characteristics inherent in longitudinal data. We applied the derived mixed-effect machine learning (MEml) framework to predict longitudinal change in glycemic control measured by hemoglobin A1c (HbA1c) among well controlled adults with type 2 diabetes. Results show that MEml is competitive with traditional GLMM, but substantially outperformed standard machine learning models that do not accoun...
Source: Journal of Biomedical Informatics - September 5, 2018 Category: Information Technology Source Type: research

Methodological variations in lagged regression for detecting physiologic drug effects in EHR data
This study found that methodological variations, such as pre-processing and representations, have a large effect on results, exposing the importance of thoroughly evaluating these components when comparing machine-learning methods.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - August 31, 2018 Category: Information Technology Source Type: research

Semantic Relation Extraction Aware of N-Gram Features from Unstructured Biomedical Text
Publication date: Available online 30 August 2018Source: Journal of Biomedical InformaticsAuthor(s): Zheng Wang, Shuo Xu, Lijun ZhuAbstractSemantic relation extraction is a crucial step of automatically constructing a knowledge graph from unstructured biomedical text. Many real-world applications can benefit from it. As unsupervised relation extraction approaches, generative probabilistic models, Rel-LDA and Type-LDA, are receiving more attention in recent years. However, these two models inherit the bag-of-word assumption of the standard LDA model, which disable the exploitation of more distinguishable n-gram features. To...
Source: Journal of Biomedical Informatics - August 31, 2018 Category: Information Technology Source Type: research

Networked Medical Data Sharing on Secure Medium - A web publishing mode for DICOM viewer with three layer authentication
Publication date: Available online 24 August 2018Source: Journal of Biomedical InformaticsAuthor(s): Sridevi Arumugham, Sundararaman Rajagopalan, John Bosco Balaguru Rayappan, Rengarajan AmirtharajanAbstractGrowing demand for e - healthcare across the globe has raised concerns towards the secure and authentication enhanced medical image sharing. One of the services offered by health informatics in hospitals include an user interface through the Local Area Network (LAN) for enabling storage and access of medical records. In this paper, a security enhanced DICOM image sharing over a LAN addressing confidentiality, integrity ...
Source: Journal of Biomedical Informatics - August 25, 2018 Category: Information Technology Source Type: research

A Multi-Level Usability Evaluation of Mobile Health Applications: A Case Study
ConclusionThe stratified view of the health IT usability evaluation framework is a useful methodological approach for the design, development, and evaluation of mHealth apps. The methodological recommendations for using the theoretical framework can inform future usability studies of mHealth apps.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - August 24, 2018 Category: Information Technology Source Type: research

Drug-Drug Interaction Extraction from Biomedical Texts Using Long Short-Term Memory Network
In this study, we present three long short-term memory (LSTM) network models, namely B-LSTM, AB-LSTM, and Joint AB-LSTM. All three models use word and position embedding as latent features; thus, they do not rely on explicit feature engineering. Furthermore, the use of a bidirectional LSTM (Bi-LSTM) network allows for extraction of implicit features from an entire sentence. The two models AB-LSTM and Joint AB-LSTM also apply attentive pooling in the Bi-LSTM layer output in order to assign weights to features. Our experimental results on the SemEval-2013 DDI extraction dataset indicate that the Joint AB-LSTM model produces ...
Source: Journal of Biomedical Informatics - August 21, 2018 Category: Information Technology Source Type: research

Probabilistic modeling personalized treatment pathways using electronic health records
ConclusionThe experimental results on a real-world data set clearly suggest that the proposed model has efficiency in mining and modeling personalized treatment pathways. We argue that the discovered treatment topics and their transition routes, as actionable knowledge that represents the practice of treating individual patients in their clinical pathways, can be further exploited to help physicians better understand their specialty and learn from previous experiences for treatment analysis and improvement.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - August 21, 2018 Category: Information Technology Source Type: research

Choosing the best algorithm for event detection based on the intended application: A conceptual framework for syndromic surveillance
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): Céline Faverjon, John BerezowskiAbstractThere is an extensive list of methods available for the early detection of an epidemic signal in syndromic surveillance data. However, there is no commonly accepted classification system for the statistical methods used for event detection in syndromic surveillance. Comparing and choosing appropriate event detection algorithms is an increasingly challenging task. Although lists of selection criteria, and statistical methods used for signal detection have been reported, selection crit...
Source: Journal of Biomedical Informatics - August 19, 2018 Category: Information Technology Source Type: research

Exploiting MEDLINE for Gene Molecular Function Prediction via NMF based Multi-Label Classification
Publication date: Available online 18 August 2018Source: Journal of Biomedical InformaticsAuthor(s): Samah Jamal Fodeh, Aditya TiwariAbstractGene ontology (GO) provides a representation of terms and categories used to describe genes and their molecular functions, cellular components and biological processes. GO has been the standard for describing the functions of specific genes in different model organisms. GO annotation, or the tagging of genes with GO terms, has mostly been a manual and time-consuming curation process. Although many automated approaches have been proposed for annotation, few have utilized knowledge avai...
Source: Journal of Biomedical Informatics - August 18, 2018 Category: Information Technology Source Type: research

A Convolutional Route to Abbreviation Disambiguation in Clinical Text
Publication date: Available online 15 August 2018Source: Journal of Biomedical InformaticsAuthor(s): Venkata Joopudi, Bharath Dandala, Murthy DevarakondaAbstractObjectiveAbbreviations sense disambiguation is a special case of word sense disambiguation. Machine learning methods based on neural networks showed promising results for word sense disambiguation [1] and, here we assess their effectiveness for abbreviation sense disambiguationMethodsConvolutional Neural Network (CNN) models were trained, one for each abbreviation, to disambiguate abbreviation senses. A reverse substitution (of long forms with short forms) method f...
Source: Journal of Biomedical Informatics - August 15, 2018 Category: Information Technology Source Type: research

Risk Prediction using Natural Language Processing of Electronic Mental Health Records in an Inpatient Forensic Psychiatry Setting
ConclusionsNLP, used in conjunction with NLP dictionaries and machine learning, predicted risk ratings on the HCR-20, START, and DASA, based on EHR content. Further research is required to ascertain the utility of NLP approaches in predicting endpoints of actual self-harm, harm to others or victimisation.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - August 14, 2018 Category: Information Technology Source Type: research

POPCORN: A web service for individual PrognOsis Prediction based on multi-center clinical data CollabORatioN without patient-level data sharing
ConclusionsThe POPCORN system can build prediction models that perform well in complex clinical application scenarios and can provide effective decision support for individual patient prognostic predictions.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - August 11, 2018 Category: Information Technology Source Type: research

Skin lesion classification with ensembles of deep convolutional neural networks
Publication date: Available online 10 August 2018Source: Journal of Biomedical InformaticsAuthor(s): Balazs HarangiAbstractSkin cancer is a major public health problem with over 123,000 newly diagnosed cases worldwide in every year. Melanoma is the deadliest form of skin cancer, responsible for over 9,000 deaths in the United States each year. Thus, reliable automatic melanoma screening systems would provide a great help for clinicians to detect the malignant skin lesions as early as possible. In the last five years, the efficiency of deep learning-based methods increased dramatically and their performances seem to outperf...
Source: Journal of Biomedical Informatics - August 11, 2018 Category: Information Technology Source Type: research

Trie-based Rule Processing for Clinical NLP: a use-case study of n-trie, making the ConText algorithm more efficient and scalable
ConclusionsThe n-trie engine is an efficient, scalable engine to support NLP rule processing and shows the potential for application in other NLP tasks beyond context detection.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - August 6, 2018 Category: Information Technology Source Type: research

Molecular Property Diagnostic Suite for Diabetes Mellitus (MPDSDM): An Integrated Web Portal for Drug Discovery and Drug Repurposing
Publication date: Available online 6 August 2018Source: Journal of Biomedical InformaticsAuthor(s): Anamika Singh Gaur, Selvaraman Nagamani, Karunakar Tanneeru, Dmitry Druzhilovskiy, Anastassia Rudik, Vladimir Poroikov, G. Narahari SastryAbstractMolecular Property Diagnostic Suite - Diabetes Mellitus (MPDSDM) is a Galaxy-based, open source disease-specific web portal for diabetes. It consists of three modules namely i) data library ii) data processing and iii) data analysis tools. The data library (target library and literature) module provide extensive and curated information about the genes involved in type 1 and type 2 ...
Source: Journal of Biomedical Informatics - August 6, 2018 Category: Information Technology Source Type: research

Choosing the best algorithm for event detection based on the intend application: a conceptual framework for syndromic surveillance
Publication date: Available online 6 August 2018Source: Journal of Biomedical InformaticsAuthor(s): Céline Faverjon, John BerezowskiAbstractThere is an extensive list of methods available for the early detection of an epidemic signal in syndromic surveillance data. However, there is no commonly accepted classification system for the statistical methods used for event detection in syndromic surveillance. Comparing and choosing appropriate event detection algorithms is an increasingly challenging task. Although lists of selection criteria, and statistical methods used for signal detection have been reported, selection...
Source: Journal of Biomedical Informatics - August 6, 2018 Category: Information Technology Source Type: research

Predict effective drug combination by deep belief network and Ontology Fingerprints
We report here a novel method based on deep belief network to predict drug synergy from gene expression, pathway and the Ontology Fingerprints—a literature derived ontological profile of genes. Using data sets provided by 2015 DREAM competition, our analysis shows that this integrative method outperforms published results from the DREAM website for 4999 drug pairs, demonstrating the feasibility of predicting drug synergy from literature and the –omics data using advanced artificial intelligence approach.Graphical abstractFig. 1. The workflow of the synergy scoring system of drug combination (Source: Journal of ...
Source: Journal of Biomedical Informatics - August 3, 2018 Category: Information Technology Source Type: research

A Markov Approach for Increasing Precision in the Assessment of Data-Intensive Behavioral Interventions
Publication date: Available online 31 July 2018Source: Journal of Biomedical InformaticsAuthor(s): Vincent Berardi, Ricardo Carretero-González, John Bellettiere, Marc A. Adams, Suzanne Hughes, Melbourne HovellAbstractHealth interventions using real-time sensing technology are characterized by intensive longitudinal data, which has the potential to enable nuanced evaluations of individuals’ responses to treatment. Existing analytic tools were not developed to capitalize on this opportunity as they typically focus on first-order findings such as changes in the level and/or slope of outcome variables over differe...
Source: Journal of Biomedical Informatics - July 31, 2018 Category: Information Technology Source Type: research

A Cognitive Systems Engineering Design Approach to Improve the Usability of Electronic Order Forms for Medical Consultation
The objective of this research was to implement a CSE design approach to develop a template that supports the cognitive needs of referring clinicians and improves referral communication.MethodsWe conducted interviews and observations with primary care providers and specialists at two major tertiary, urban medical facilities. Using qualitative analysis, we identified cognitive requirements and design guidelines. Next, we designed user interface (UI) prototypes and compared their usability with that of a currently implemented UI at a major Midwestern medical facility.ResultsPhysicians’ cognitive challenges were summari...
Source: Journal of Biomedical Informatics - July 31, 2018 Category: Information Technology Source Type: research

An Approach to Automatic Process Deviation Detection in a Time-Critical Clinical Process
ConclusionOur approach to automatic deviation detection provides a method for identifying repeated, omitted and out-of-sequence activities that can be included in the design of decision support systems for complex medical processes. Our findings show the importance of assessing detected deviations for repairing a knowledge-driven model that best represents “work as done.”Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 31, 2018 Category: Information Technology Source Type: research

Persuasive Technology in Biomedical Informatics
Publication date: Available online 31 July 2018Source: Journal of Biomedical InformaticsAuthor(s): M.Sriram Iyengar, Harri Oinas-Kukkonen, Khin Than Win (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 31, 2018 Category: Information Technology Source Type: research

Cover 1/Spine
Publication date: August 2018Source: Journal of Biomedical Informatics, Volume 84Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 31, 2018 Category: Information Technology Source Type: research

Cover 2: Editorial Board
Publication date: August 2018Source: Journal of Biomedical Informatics, Volume 84Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 31, 2018 Category: Information Technology Source Type: research

fmi-ii: Table of Contents
Publication date: August 2018Source: Journal of Biomedical Informatics, Volume 84Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 31, 2018 Category: Information Technology Source Type: research

An unsupervised machine learning method for discovering patient clusters based on genetic signatures
ConclusionOnce links are drawn between clusters and clinically relevant outcomes, Immunochip data can be used to classify high-risk and newly diagnosed chronic disease patients into known clusters for predictive value. Further investigation can extend beyond pathway analysis to evaluate these clusters for clinical significance of genetically related characteristics such as age of onset, disease course, heritability, and response to treatment.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 29, 2018 Category: Information Technology Source Type: research

A beginner’s guide to avoiding Protected Health Information (PHI) issues in clinical research – With how-to’s in REDCap Data Management Software
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): Marjorie A. Bowman, Rose A. MaxwellAbstractProtecting personally identifiable information is important in clinical research. The authors, two faculty members involved in developing and implementing research infrastructure for a medical school, observed challenges novice researchers encountered in recognizing, collecting, and managing Protected Health Information (PHI) for clinical research. However, we had difficulty finding resources that provide practical strategies for novice clinical researchers for this topic. Common issues ...
Source: Journal of Biomedical Informatics - July 29, 2018 Category: Information Technology Source Type: research

A data-driven method to detect adverse drug events from prescription data
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): Chen Zhan, Elizabeth Roughead, Lin Liu, Nicole Pratt, Jiuyong LiAbstractDrug safety issues such as Adverse Drug Events (ADEs) can cause serious consequences for the public. The clinical trials that are undertaken to assess medicine efficacy and safety prior to marketing, generally, may provide sufficient samples for discovering common ADEs. However, more samples are needed to detect infrequent and rare events. Additionally, clinical trials may not include all subgroups of patients. For these reasons, post-marketing surveillance o...
Source: Journal of Biomedical Informatics - July 29, 2018 Category: Information Technology Source Type: research

Mining features for biomedical data using clustering tree ensembles
Publication date: September 2018Source: Journal of Biomedical Informatics, Volume 85Author(s): Konstantinos Pliakos, Celine VensAbstractThe volume of biomedical data available to the machine learning community grows very rapidly. A rational question is how informative these data really are or how discriminant the features describing the data instances are. Several biomedical datasets suffer from lack of variance in the instance representation, or even worse, contain instances with identical features and different class labels. Indisputably, this directly affects the performance of machine learning algorithms, as well as th...
Source: Journal of Biomedical Informatics - July 29, 2018 Category: Information Technology Source Type: research

How does normalization impact RNA-seq disease diagnosis?
In this study, we investigate this problem by analyzing structured big data: RNA-seq data acquired from the TCGA portal for its popularity in RNA-seq disease diagnosis. We propose a novel normalization effect test algorithm, diagnostic index (d-index), and data entropy to analyze and evaluate the impacts of normalization on RNA-seq disease diagnosis by using state-of-the-art machine learning models. Furthermore, we present an original visualization analysis to compare the performance of normalized data versus raw data.We have found that normalized data yields generally an equivalent or even lower level diagnosis than its r...
Source: Journal of Biomedical Informatics - July 22, 2018 Category: Information Technology Source Type: research

When to re-order laboratory tests? Learning laboratory test shelf-life
Publication date: Available online 20 July 2018Source: Journal of Biomedical InformaticsAuthor(s): Gal Levy-Fix, Sharon Lipsky Gorman, Jorge L. Sepulveda, Noémie ElhadadAbstractMost laboratory results are valid for only a certain time period (laboratory tests shelf-life), after which they are outdated and the test needs to be re-administered. Currently, laboratory test shelf-lives are not centrally available anywhere but the implicit knowledge of doctors. In this work we propose an automated method to learn laboratory test-specific shelf-life by identifying prevalent laboratory test order patterns in electronic heal...
Source: Journal of Biomedical Informatics - July 21, 2018 Category: Information Technology Source Type: research

Development of machine translation technology for assisting health communication: A systematic review
ConclusionsMT is currently being developed primarily through pilot studies to improve multilingual communication in health settings and to increase access to health resources for a variety of languages. However, continued concerns about accuracy limit the deployment of MT systems in these settings. The variety of piloted systems and the lack of shared evaluation criteria will likely continue to impede adoption in health settings, where excellent accuracy and a strong evidence base are critical. Greater translation accuracy and use of standard evaluation criteria would encourage deployment of MT into health settings. For no...
Source: Journal of Biomedical Informatics - July 20, 2018 Category: Information Technology Source Type: research

A scalable method for supporting multiple patient cohort discovery projects using i2b2
Publication date: August 2018Source: Journal of Biomedical Informatics, Volume 84Author(s): Evan T. Sholle, Marcos A. Davila, Joseph Kabariti, Julian Z. Schwartz, Vinay I. Varughese, Curtis L. Cole, Thomas R. CampionAbstractAlthough i2b2, a popular platform for patient cohort discovery using electronic health record (EHR) data, can support multiple projects specific to individual disease areas or research interests, the standard approach for doing so duplicates data across projects, requiring additional disk space and processing time, which limits scalability. To address this deficiency, we developed a novel approach that ...
Source: Journal of Biomedical Informatics - July 19, 2018 Category: Information Technology Source Type: research

Relief-Based Feature Selection: Introduction and Review
Publication date: Available online 18 July 2018Source: Journal of Biomedical InformaticsAuthor(s): Ryan J. Urbanowicz, Melissa Meeker, William La Cava, Randal S. Olson, Jason H. MooreAbstractFeature selection plays a critical role in biomedical data mining, driven by increasing feature dimensionality in target problems and growing interest in advanced but computationally expensive methodologies able to model complex associations. Specifically, there is a need for feature selection methods that are computationally efficient, yet sensitive to complex patterns of association, e.g. interactions, so that informative features ar...
Source: Journal of Biomedical Informatics - July 19, 2018 Category: Information Technology Source Type: research

Benchmarking Relief-Based Feature Selection Methods for Bioinformatics Data Mining
Publication date: Available online 17 July 2018Source: Journal of Biomedical InformaticsAuthor(s): Ryan J. Urbanowicz, Randal S. Olson, Peter Schmitt, Melissa Meeker, Jason H. MooreAbstractModern biomedical data mining requires feature selection methods that can (1) be applied to large scale feature spaces (e.g. ‘omics’ data), (2) function in noisy problems, (3) detect complex patterns of association (e.g. gene-gene interactions), (4) be flexibly adapted to various problem domains and data types (e.g. genetic variants, gene expression, and clinical data) and (5) are computationally tractable. To that end, this ...
Source: Journal of Biomedical Informatics - July 18, 2018 Category: Information Technology Source Type: research

Classification of ADHD with bi-objective optimization
Publication date: August 2018Source: Journal of Biomedical Informatics, Volume 84Author(s): Lizhen Shao, Yadong Xu, Dongmei FuAbstractAttention Deficit Hyperactive Disorder (ADHD) is one of the most common diseases in school aged children. In this paper, we consider using fMRI data with classification techniques to aid the diagnosis of ADHD and propose a bi-objective ADHD classification scheme based on L1-norm support vector machine (SVM). In our classification model, two objectives, namely, the margin of separation and the empirical error are considered at the same time. Then the normal boundary intersection (NBI) method ...
Source: Journal of Biomedical Informatics - July 18, 2018 Category: Information Technology Source Type: research

Transferability of Artificial Neural Networks for Clinical Document Classification Across Hospitals: A Case Study on Abnormality Detection from Radiology Reports
ConclusionTransferring a pre-trained CNN model generated in one hospital to another facilitates application of machine learning approaches that alleviate both hospital-specific feature engineering and training data.Graphical abstract (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 18, 2018 Category: Information Technology Source Type: research

Cover 1/Spine
Publication date: July 2018Source: Journal of Biomedical Informatics, Volume 83Author(s): (Source: Journal of Biomedical Informatics)
Source: Journal of Biomedical Informatics - July 17, 2018 Category: Information Technology Source Type: research