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Journal of Biomedical Informatics

Zhipeng Jiang, Chao Zhao, Bin He, Yi Guan, Jingchi Jiang
The CEGS N-GRID 2016 Shared Task 1 in Clinical Natural Language Processing focuses on the de-identification of psychiatric evaluation records. This paper describes two participating systems of our team, based on conditional random fields (CRFs) and long short-term memory networks (LSTMs). A pre-processing module was introduced for sentence detection and tokenization before de-identification. For CRFs, manually extracted rich features were utilized to train the model. For LSTMs, a character-level bi-directional LSTM network was applied to represent tokens and classify tags for each token, following which a decoding layer was stacked to decode the most probable protected health information (PHI) terms...
October 12, 2017: Journal of Biomedical Informatics
Enver Zerem
It is generally accepted that the scientific impact factor (Web of Science) and the total number of citations of the articles published in a journal, are the most relevant parameters of the journal's significance. However, the significance of scientists is much more complicated to establish and the value of their scientific production can not be directly reflected by the importance of the journals in which their articles are published. Evaluating the significance of scientists' accomplishments involves more complicated metrics than just their publication records...
October 11, 2017: Journal of Biomedical Informatics
Lingyun Luo, Ling Tong, Xiaoxi Zhou, Jose L V Mejino, Chunping Ouyang, Yongbin Liu
Organizing the descendants of a concept under a particular semantic relationship may be rather arbitrarily carried out during the manual creation processes of large biomedical terminologies, resulting in imbalances in relationship granularity. This work aims to propose scalable models towards systematically evaluating the granularity balance of semantic relationships. We first utilize "parallel concepts set (PCS)" and two features (the length and the strength) of the paths between PCSs to design the general evaluation models, based on which we propose eight concrete evaluation models generated by two specific types of PCSs: single concept set and symmetric concepts set...
October 4, 2017: Journal of Biomedical Informatics
Alexander Shknevsky, Yuval Shahar, Robert Moskovitch
Increasingly, frequent temporal patterns discovered in longitudinal patient records are proposed as features for classification and prediction, and as means to cluster patient clinical trajectories. However, to justify that, we must demonstrate that most frequent temporal patterns are indeed consistently discoverable within the records of different patient subsets within similar patient populations. We have developed several measures for the consistency of the discovery of temporal patterns. We focus on time-interval relations patterns (TIRPs) that can be discovered within different subsets of the same patient population...
October 4, 2017: Journal of Biomedical Informatics
Courtland VanDam, Shaheen Kanthawala, Wanda Pratt, Joyce Chai, Jina Huh
Patients with chronic health conditions use online health communities to seek support and information to help manage their condition. For clinically related topics, patients can benefit from getting opinions from clinical experts, and many are concerned about misinformation and biased information being spread online. However, a large volume of community posts makes it challenging for moderators and clinical experts, if there are any, to provide necessary information. Automatically identifying forum posts that need validated clinical resources can help online health communities efficiently manage content exchange...
October 3, 2017: Journal of Biomedical Informatics
Sun Kim, Nicolas Fiorini, W John Wilbur, Zhiyong Lu
The main approach of traditional information retrieval (IR) is to examine how many words from a query appear in a document. A drawback of this approach, however, is that it may fail to detect relevant documents where no or only few words from a query are found. The semantic analysis methods such as LSA (latent semantic analysis) and LDA (latent Dirichlet allocation) have been proposed to address the issue, but their performance is not superior compared to common IR approaches. Here we present a query-document similarity measure motivated by the Word Mover's Distance...
October 3, 2017: Journal of Biomedical Informatics
Lena Mamykina, Elizabeth Heitkemper, Arlene M Smaldone, Rita Kukafka, Heather Cole-Lewis, Patricia G Davidson, Elizabeth D Mynatt, Andrea Cassells, Jonathan N Tobin, George Hripcsak
OBJECTIVE: To outline new design directions for informatics solutions that facilitate personal discovery with self-monitoring data. We investigate this question in the context of chronic disease self-management with the focus on type 2 diabetes. MATERIALS AND METHODS: We conducted an observational qualitative study of discovery with personal data among adults attending a diabetes self-management education (DSME) program that utilized a discovery-based curriculum...
September 30, 2017: Journal of Biomedical Informatics
Keith Danahey, Brittany A Borden, Brian Furner, Patrick Yukman, Sheena Hussain, Donald Saner, Samuel L Volchenboum, Mark J Ratain, Peter H O'Donnell
BACKGROUND: A barrier to the use of genomic information during prescribing is the limited number of software solutions that combine a user-friendly interface with complex medical data. We built and designed an online, secure, electronic custom interface termed the Genomic Prescribing System (GPS). METHODS: Actionable pharmacogenomic (PGx) information was reviewed, collected, and stored in the back-end of GPS to enable creation of customized drug- and variant-specific clinical decision support (CDS) summaries...
September 26, 2017: Journal of Biomedical Informatics
Chunrui Xu, Li Ge, Yusen Zhang, Matthias Dehmer, Ivan Gutman
As therapeutic peptides have been taken into consideration in disease therapy in recent years, many biologists spent time and labor to verify various functional peptides from a large number of peptide sequences. In order to reduce the workload and increase the efficiency of identification of functional proteins, we propose a sequence-based model, q-FP (functional peptide prediction based on the q-Wiener Index), capable of recognizing potentially functional proteins. We extract three types of features by mixing graphic representation and statistical indices based on the q-Wiener index and physicochemical properties of amino acids...
September 25, 2017: Journal of Biomedical Informatics
Sungrae Park, Doosup Choi, Minki Kim, Wonchul Cha, Chuhyun Kim, Il-Chul Moon
Wide variance exists among individuals and institutions for treating patients with medicine. This paper analyzes prescription patterns using a topic model with more than four million prescriptions. Specifically, we propose the disease-medicine pattern model (DMPM) to extract patterns from a large collection of insurance data by considering disease codes joined with prescribed medicines. We analyzed insurance prescription data from 2011 with DMPM and found prescription patterns that could not be identified by traditional simple disease classification, such as the International Classification of Diseases (ICD)...
September 25, 2017: Journal of Biomedical Informatics
Di Qi, Karthikeyan Panneerselvam, Woojin Ahn, Venkata Arikatla, Andinet Enquobahrie, Suvranu De
BACKGROUND: Suturing with intracorporeal knot-tying is one of the five tasks of the Fundamentals of Laparoscopic Surgery (FLS), which is a pre-requisite for board certification in general surgery. This task involves placing a short suture through two marks in a penrose drain and then tying a double-throw knot followed by two single-throw knots using two needle graspers operated by both hands. A virtual basic laparoscopic skill trainer (VBLaST(©)) is being developed to represent the virtual versions of the FLS tasks, including automated, real time performance measurement and feedback...
September 22, 2017: Journal of Biomedical Informatics
Christopher G Scully, Chathuri Daluwatte
Patient monitoring algorithms that analyze multiple features from physiological signals can produce an index that serves as a predictive or prognostic measure for a specific critical health event or physiological instability. Classical detection metrics such as sensitivity and positive predictive value are often used to evaluate new patient monitoring indices for such purposes, but since these metrics do not take into account the continuous nature of monitoring, the assessment of a warning system to notify a user of a critical health event remains incomplete...
September 20, 2017: Journal of Biomedical Informatics
David Riaño, Wilfrido Ortega
The high prevalence of multimorbid cases is a challenge for Health-Care Systems today. Clinical practice guidelines are the means to register and transmit the available evidence-based medical knowledge concerning concrete diseases. Several computer languages have been defined to represent this knowledge in a way that computers could use to help physicians in the daily practice of medicine. The generation of guidelines for all possible multimorbidities entails several issues that are difficult to address. Consequently, numerous medical informatics technologies have appeared merging computer information structures in a way that the treatment knowledge about single diseases could be combined in order to deliver health-care to patients suffering from multimorbidity...
September 20, 2017: Journal of Biomedical Informatics
Sarah Collins, Stephanie Klinkenberg-Ramirez, Kira Tsivkin, Perry L Mar, Dina Iskhakova, Hari Nandigam, Lipika Samal, Roberto A Rocha
OBJECTIVE: Develop a prototype of an interprofessional terminology and information model infrastructure that can enable care planning applications to facilitate patient-centered care, learn care plan linkages and associations, provide decision support, and enable automated, prospective analytics. DESIGN: The study steps included a 3 step approach: 1) Process model and clinical scenario development, and 2) Requirements analysis, and 3) Development and validation of information and terminology models...
September 19, 2017: Journal of Biomedical Informatics
Robert Moskovitch, Fernanda Polubriaginof, Aviram Weiss, Patrick Ryan, Nicholas Tatonetti
Prediction of medical events, such as clinical procedures, is essential for preventing disease, understanding disease mechanism, and increasing patient quality of care. Although longitudinal clinical data from Electronic Health Records provides opportunities to develop predictive models, the use of these data faces significant challenges. Primarily, while the data are longitudinal and represent thousands of conceptual events having duration, they are also sparse, complicating the application of traditional analysis approaches...
August 17, 2017: Journal of Biomedical Informatics
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 3days 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
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
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
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
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
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