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Journal of Biomedical Informatics

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https://www.readbyqxmd.com/read/28822857/exploring-associations-of-clinical-and-social-parameters-with-violent-behaviors-among-psychiatric-patients
#1
Hong-Jie Dai, Emily Chia-Yu Su, Mohy Uddin, Jitendra Jonnagaddala, Chi-Shin Wu, Shabbir Syed-Abdul
Evidence has revealed interesting associations of clinical and social parameters with violent behaviors of patients with psychiatric disorders. Men are more violent preceding and during hospitalization, whereas women are more violent than men throughout the 3 days following a hospital admission. It has also been proven that mental disorders may be a consistent risk factor for the occurrence of violence. In order to better understand violent behaviors of patients with psychiatric disorders, it is important to investigate both the clinical symptoms and psychosocial factors that accompany violence in these patients...
August 16, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28803947/monitoring-stress-with-a-wrist-device-using-context
#2
Martin Gjoreski, Mitja Luštrek, Matjaž Gams, Hristijan Gjoreski
Being able to detect stress as it occurs can greatly contribute to dealing with its negative health and economic consequences. However, detecting stress in real life with an unobtrusive wrist device is a challenging task. The objective of this study is to develop a method for stress detection that can accurately, continuously and unobtrusively monitor psychological stress in real life. First, we explore the problem of stress detection using machine learning and signal processing techniques in laboratory conditions, and then we apply the extracted laboratory knowledge to real-life data...
August 10, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28802838/identification-of-immune-correlates-of-protection-in-shigella-infection-by-application-of-machine-learning
#3
Jorge M Arevalillo, Marcelo B Sztein, Karen L Kotloff, Myron M Levine, Jakub K Simon
BACKGROUND: Immunologic correlates of protection are important in vaccine development because they give insight into mechanisms of protection, assist in the identification of promising vaccine candidates, and serve as endpoints in bridging clinical vaccine studies. Our goal is the development of a methodology to identify immunologic correlates of protection using the Shigella challenge as a model. METHODS: The proposed methodology utilizes the Random Forests (RF) machine learning algorithm as well as Classification and Regression Trees (CART) to detect immune markers that predict protection, identify interactions between variables, and define optimal cutoffs...
August 9, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28802837/development-of-simulation-optimization-methods-for-solving-patient-referral-problems-in-the-hospital-collaboration-environment
#4
Ping-Shun Chen, Ming-Han Lin
This research studied a patient referral problem among multiple cooperative hospitals for sharing imaging services' referrals. The proposed problem consisted of many types of patients and the uncertainty associated with the number of patients of each type, patients' arrival time, and patients' medical operation time, leading to a difficulty in finding solutions due to the uncertain environment. This research used system simulation to construct a model and develop a simulation optimization method, combining the heuristic algorithm (patient referral mechanism) with the particle swarm optimization (PSO) method, to determine a better way to refer patients from one hospital (referring hospital) to another (recipient hospital) to receive certain imaging services...
August 9, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28797710/a-bayesian-system-to-detect-and-characterize-overlapping-outbreaks
#5
John M Aronis, Nicholas E Millett, Michael M Wagner, Fuchiang Tsui, Ye Ye, Jeffrey P Ferraro, Peter J Haug, Per H Gesteland, Gregory F Cooper
Outbreaks of infectious diseases such as influenza are a significant threat to human health. Because there are different strains of influenza which can cause independent outbreaks, and influenza can affect demographic groups at different rates and times, there is a need to recognize and characterize multiple outbreaks of influenza. This paper describes a Bayesian system that uses data from emergency department patient care reports to create epidemiological models of overlapping outbreaks of influenza. Clinical findings are extracted from patient care reports using natural language processing...
August 7, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28797709/word-embeddings-and-recurrent-neural-networks-based-on-long-short-term-memory-nodes-in-supervised-biomedical-word-sense-disambiguation
#6
Antonio Jimeno Yepes
Word sense disambiguation helps identifying the proper sense of ambiguous words in text. With large terminologies such as the UMLS Metathesaurus ambiguities appear and highly effective disambiguation methods are required. Supervised learning algorithm methods are used as one of the approaches to perform disambiguation. Features extracted from the context of an ambiguous word are used to identify the proper sense of such a word. The type of features have an impact on machine learning methods, thus affect disambiguation performance...
August 7, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28782602/hiding-electronic-patient-record-epr-in-medical-images-a-high-capacity-and-computationally-efficient-technique-for-e-healthcare-applications
#7
Nazir A Loan, Shabir A Parah, Javaid A Sheikh, Jahangir A Akhoon, Ghulam M Bhat
A high capacity and semi-reversible data hiding scheme based on Pixel Repetition Method (PRM) and hybrid edge detection for scalable medical images has been proposed in this paper. PRM has been used to scale up the small sized image (seed image) and hybrid edge detection ensures that no important edge information is missed. The scaled up version of seed image has been divided into 2×2 non overlapping blocks. In each block there is one seed pixel whose status decides the number of bits to be embedded in the remaining three pixels of that block...
August 3, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28756161/ctpath-demixing-pathway-crosstalk-effect-from-transcriptomics-data-for-differential-pathway-identification
#8
Xin-Ping Xie, Bin Gan, Wulin Yang, Hong-Qiang Wang
Identifying differentially expressed pathways (DEPs) plays important roles in understanding tumor etiology and promoting clinical treatment of cancer or other diseases. By assuming gene expression to be a sparse non-negative linear combination of hidden pathway signals, we propose a pathway crosstalk-based transcriptomics data analysis method (ctPath) for identifying differentially expressed pathways. Biologically, pathways of different functions work in concert at the systematic level. The proposed method interrogates the crosstalks between pathways and discovers hidden pathway signals by mapping high-dimensional transcriptomics data into a low-dimensional pathway space...
July 26, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28756160/a-cascaded-approach-for-chinese-clinical-text-de-identification-with-less-annotation-effort
#9
Zhe Jian, Xusheng Guo, Shijian Liu, Handong Ma, Shaodian Zhang, Rui Zhang, Jianbo Lei
With rapid adoption of Electronic Health Records (EHR) in China, an increasing amount of clinical data has been available to support clinical research. Clinical data secondary use usually requires de-identification of personal information to protect patient privacy. Since manually de-identification of free clinical text requires significant amount of human work, developing an automated de-identification system is necessary. While there are many de-identification systems available for English clinical text, designing a de-identification system for Chinese clinical text faces many challenges such as unavailability of necessary lexical resources and sparsity of patient health information (PHI) in Chinese clinical text...
July 26, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28756159/automatic-identification-of-high-impact-articles-in-pubmed-to-support-clinical-decision-making
#10
Jiantao Bian, Mohammad Amin Morid, Siddhartha Jonnalagadda, Gang Luo, Guilherme Del Fiol
OBJECTIVES: The practice of evidence-based medicine involves integrating the latest best available evidence into patient care decisions. Yet, critical barriers exist for clinicians' retrieval of evidence that is relevant for a particular patient from primary sources such as randomized controlled trials and meta-analyses. To help address those barriers, we investigated machine learning algorithms that find clinical studies with high clinical impact from PubMed®. METHODS: Our machine learning algorithms use a variety of features including bibliometric features (e...
July 26, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28754523/development-and-classification-of-a-robust-inventory-of-near-real-time-outcome-measurements-for-assessing-information-technology-interventions-in-health-care
#11
Tiago K Colicchio, Guilherme Del Fiol, Debra L Scammon, Watson A Bowes, Julio C Facelli, Scott P Narus
OBJECTIVE: To develop and classify an inventory of near real-time outcome measures for assessing information technology (IT) interventions in health care and assess their relevance as perceived by experts in the field. MATERIALS AND METHODS: To verify the robustness and coverage of a previously published inventory of measures and taxonomy, we conducted semi-structured interviews with clinical and administrative leaders from a large care delivery system to collect suggestions of outcome measures that can be calculated with data available in electronic format for near real-time monitoring of EHR implementations...
July 25, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28754522/finding-patients-using-similarity-measures-in-a-rare-diseases-oriented-clinical-data-warehouse-dr-warehouse-and-the-needle-in-the-needle-stack
#12
Garcelon Nicolas, Neuraz Antoine, Benoit Vincent, Salomon Rémi, Kracker Sven, Suarez Felipe, Bahi-Buisson Nadia, Hadj-Rabia Smail, Fischer Alain, Munnich Arnold, Burgun Anita
OBJECTIVE: In the context of rare diseases, it may be helpful to detect patients with similar medical histories, diagnoses and outcomes from a large number of cases with automated methods. To reduce the time to find new cases, we developed a method to find similar patients given an index case leveraging data from the electronic health records. MATERIALS AND METHODS: We used the clinical data warehouse of a children academic hospital in Paris, France (Necker-Enfants Malades), containing about 400,000 patients...
July 25, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28729030/natural-language-processing-systems-for-capturing-and-standardizing-unstructured-clinical-information-a-systematic-review
#13
REVIEW
Kory Kreimeyer, Matthew Foster, Abhishek Pandey, Nina Arya, Gwendolyn Halford, Sandra F Jones, Richard Forshee, Mark Walderhaug, Taxiarchis Botsis
We followed a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) systems that generate structured information from unstructured free text. Seven literature databases were searched with a query combining the concepts of natural language processing and structured data capture. Two reviewers screened all records for relevance during two screening phases, and information about clinical NLP systems was collected from the final set of papers...
July 17, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28723580/quality-assurance-of-chemical-ingredient-classification-for-the-national-drug-file-reference-terminology
#14
Ling Zheng, Hasan Yumak, Ling Chen, Christopher Ochs, James Geller, Joan Kapusnik-Uner, Yehoshua Perl
The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology consisting of several classification hierarchies on top of an extensive collection of drug concepts. These hierarchies provide important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects. Within NDF-RT such information is represented using tens of thousands of roles connecting drugs to classifications. In previous studies, we have introduced various kinds of Abstraction Networks to summarize the content and structure of terminologies in order to facilitate their visual comprehension, and support quality assurance of terminologies...
July 16, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28723579/elucidating-high-dimensional-cancer-hallmark-annotation-via-enriched-ontology
#15
Shankai Yan, Ka-Chun Wong
MOTIVATION: Cancer hallmark annotation is a promising technique that could discover novel knowledge about cancer from the biomedical literature. The automated annotation of cancer hallmarks could reveal relevant cancer transformation processes in the literature or extract the articles that correspond to the cancer hallmark of interest. It acts as a complementary approach that can retrieve knowledge from massive text information, advancing numerous focused studies in cancer research. Nonetheless, the high-dimensional nature of cancer hallmark annotation imposes a unique challenge...
July 16, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28720438/on-the-utility-of-3d-hand-cursors-to-explore-medical-volume-datasets-with-a-touchless-interface
#16
Daniel Simões Lopes, Pedro Duarte de Figueiredo Parreira, Soraia Figueiredo Paulo, Vitor Nunes, Paulo Amaral Rego, Manuel Cassiano Neves, Pedro Silva Rodrigues, Joaquim Armando Jorge
Analyzing medical volume datasets requires interactive visualization so that users can extract anatomo-physiological information in real-time. Conventional volume rendering systems rely on 2D input devices, such as mice and keyboards, which are known to hamper 3D analysis as users often struggle to obtain the desired orientation that is only achieved after several attempts. In this paper, we address which 3D analysis tools are better performed with 3D hand cursors operating on a touchless interface comparatively to a 2D input devices running on a conventional WIMP interface...
July 15, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28712748/chi-a-contemporaneous-health-index-for-degenerative-disease-monitoring-using-longitudinal-measurements
#17
Yijun Huang, Qiang Meng, Heather Evans, William Lober, Yu Cheng, Xiaoning Qian, Ji Liu, Shuai Huang
In this paper, we develop a novel formulation for contemporaneous patient risk monitoring by exploiting the emerging data-rich environment in many healthcare applications, where an abundance of longitudinal data that reflect the degeneration of the health condition can be continuously collected. Our objective, and the developed formulation, is fundamentally different from many existing risk score models for different healthcare applications, which mostly focus on predicting the likelihood of a certain outcome at a pre-specified time...
July 13, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28711679/reproducibility-of-studies-on-text-mining-for-citation-screening-in-systematic-reviews-evaluation-and-checklist
#18
Babatunde Kazeem Olorisade, Pearl Brereton, Peter Andras
CONTEXT: Independent validation of published scientific results through study replication is a pre-condition for accepting the validity of such results. In computation research, full replication is often unrealistic for independent results validation, therefore, study reproduction has been justified as the minimum acceptable standard to evaluate the validity of scientific claims. The application of text mining techniques to citation screening in the context of systematic literature reviews is a relatively young and growing computational field with high relevance for software engineering, medical research and other fields...
July 12, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28709856/developing-smartphone-apps-for-behavioural-studies-the-alcorisk-app-case-study
#19
Anthony Smith, Kristy de Salas, Ian Lewis, Benjamin Schüz
Advances in mobile technology and significantly increasing utilization of mobile devices such as smartphones and tablets have resulted in a paradigm shift from PC-centric computing to mobile computing. The results of careful analysis conducted of this mobile landscape indicate that there is a growing demand for smart, user-centric, situation-aware mobile software. Invariably, concomitant with this demand is the need for methodologies that can provide support the development of this type of software. In this paper, we propose a semantic framework, called the mobile situation-aware framework, which supports efficient modeling, construction, processing, management, and inference of mobile situation information...
July 11, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28694119/recurrent-neural-networks-for-classifying-relations-in-clinical-notes
#20
Yuan Luo
We proposed the first models based on recurrent neural networks (more specifically Long Short-Term Memory - LSTM) for classifying relations from clinical notes. We tested our models on the i2b2/VA relation classification challenge dataset. We showed that our segment LSTM model, with only word embedding feature and no manual feature engineering, achieved a micro-averaged f-measure of 0.661 for classifying medical problem-treatment relations, 0.800 for medical problem-test relations, and 0.683 for medical problem-medical problem relations...
July 7, 2017: Journal of Biomedical Informatics
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