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Journal of Biomedical Informatics

Anet Aselmaa, Marcel van Herk, Anne Laprie, Ursula Nestle, Irina Götz, Nicole Wiedenmann, Tanja Schimek-Jasch, Francois Picaud, Charlotte Syrykh, Leonel V Cagetti, Maria Jolnerovski, Yu Song, Richard H M Goossens
Sensemaking theories help designers understand the cognitive processes of a user when he/she performs a complicated task. This paper introduces a two-step approach of incorporating sensemaking support within the design of health information systems by: 1) modeling the sensemaking process of physicians while performing a task, and 2) identifying software interaction design requirements that support sensemaking based on this model. The two-step approach is presented based on a case study of the tumor contouring clinical task for radiotherapy planning...
December 5, 2016: Journal of Biomedical Informatics
Charles Nicholson, Leslie Goodwin, Corey Clark
A new search heuristic, Divided Neighborhood Exploration Search, designed to be used with inference algorithms such as Bayesian networks to improve on the reverse engineering of gene regulatory networks is presented. The approach systematically moves through the search space to find topologies representative of gene regulatory networks that are more likely to explain microarray data. In empirical testing it is demonstrated that the novel method is superior to the widely employed greedy search techniques in both the quality of the inferred networks and computational time...
December 2, 2016: Journal of Biomedical Informatics
Jing Zhao, Panagiotis Papapetrou, Lars Asker, Henrik Boström
Electronic health records contain large amounts of longitudinal data that are valuable for biomedical informatics research. The application of machine learning is a promising alternative to manual analysis of such data. However, the complex structure of the data, which includes clinical events that are unevenly distributed over time, poses a challenge for standard learning algorithms. Some approaches to modeling temporal data rely on extracting single values from time series; however, this leads to the loss of potentially valuable sequential information...
December 2, 2016: Journal of Biomedical Informatics
Joanna Abraham, Thomas Kannampallil, Vignesh Srinivasan, William Galanter, Gail Tagney, Trevor Cohen
OBJECTIVE: We develop and evaluate a methodological approach to measure the degree and nature of overlap in handoff communication content within and across clinical professions. This extensible, exploratory approach relies on combining techniques from conversational analysis and distributional semantics. MATERIALS AND METHODS: We audio-recorded handoff communication of residents and nurses on the General Medicine floor of a large academic hospital (n=120 resident and n=120 nurse handoffs)...
November 29, 2016: Journal of Biomedical Informatics
Joshua Frisby, Vernon Smith, Stephen Traub, Vimla L Patel
Hospital Emergency Departments (EDs) frequently experience crowding. One of the factors that contributes to this crowding is the "door to doctor time", which is the time from a patient's registration to when the patient is first seen by a physician. This is also one of the Meaningful Use (MU) performance measures that emergency departments report to the Center for Medicare and Medicaid Services (CMS). Current documentation methods for this measure are inaccurate due to the imprecision in manual data collection...
November 29, 2016: Journal of Biomedical Informatics
Alissa L Russ, Brittany L Melton, Joanne K Daggy, Jason J Saleem
BACKGROUND: Prescribers commonly receive alerts during medication ordering. Prescribers work in a complex, time-pressured environment; to enhance the effectiveness of safety alerts, the effort needed to cognitively process these alerts should be minimized. Methods to evaluate the extent to which computerized alerts support prescribers' information processing are lacking. OBJECTIVE: To develop a methodological protocol to assess the extent to which alerts support prescribers' information processing at-a-glance; specifically, the incorporation of information into working memory...
November 28, 2016: Journal of Biomedical Informatics
Marijn Zilverschoon, Koen L Vincken, Ronald L A W Bleys
INTRODUCTION: Virtual 3D models are powerful tools for teaching anatomy. At the present day, there are a lot of different digital anatomy models, most of these commercial applications are based on a 3D model of a human body reconstructed from images with a 1 millimeter intervals. The use of even smaller intervals may result in more details and more realistic appearances of 3D anatomy models. The aim of this study was to create a realistic and highly detailed 3D model of the hand and wrist based on small interval cross-sectional images, suitable for undergraduate and postgraduate teaching purposes with the possibility to perform a virtual dissection in an educational application...
November 21, 2016: Journal of Biomedical Informatics
Liqin Wang, Guilherme Del Fiol, Bruce E Bray, Peter J Haug
OBJECTIVE: Healthcare communities have identified a significant need for disease-specific information. Disease-specific ontologies are useful in assisting the retrieval of disease-relevant information from various sources. However, building these ontologies is labor intensive. Our goal is to develop a system for an automated generation of disease-pertinent concepts from a popular knowledge resource for the building of disease-specific ontologies. METHODS: A pipeline system was developed with an initial focus of generating disease-specific treatment vocabularies...
November 16, 2016: Journal of Biomedical Informatics
Archana Prabahar, Jeyakumar Natarajan
MicroRNAs are a class of small non-coding regulatory RNA molecules that modulate the expression of several genes at post-transcriptional level and play a vital role in disease pathogenesis. Recent research shows that a range of miRNAs are involved in the regulation of immunity and its deregulation results in immune mediated diseases such as cancer, inflammation and autoimmune diseases. Computational discovery of these immune miRNAs using a set of specific features is highly desirable. In the current investigation, we present a SVM based classification system which uses a set of novel network based topological and motif features in addition to the baseline sequential and structural features to predict immune specific miRNAs from other non-immune miRNAs...
November 15, 2016: Journal of Biomedical Informatics
Vasa Curcin, Elliot Fairweather, Roxana Danger, Derek Corrigan
Decision support systems are used as a method of promoting consistent guideline-based diagnosis supporting clinical reasoning at point of care. However, despite the availability of numerous commercial products, the wider acceptance of these systems has been hampered by concerns about diagnostic performance and a perceived lack of transparency in the process of generating clinical recommendations. This resonates with the Learning Health System paradigm that promotes data-driven medicine relying on routine data capture and transformation, which also stresses the need for trust in an evidence-based system...
November 14, 2016: Journal of Biomedical Informatics
Giorgos Poulis, Grigorios Loukides, Spiros Skiadopoulos, Aris Gkoulalas-Divanis
Publishing data about patients that contain both demographics and diagnosis codes is essential to perform large-scale, low-cost medical studies. However, preserving the privacy and utility of such data is challenging, because it requires: (i) guarding against identity disclosure (re-identification) attacks based on both demographics and diagnosis codes, (ii) ensuring that the anonymized data remain useful in intended analysis tasks, and (iii) minimizing the information loss, incurred by anonymization, to preserve the utility of general analysis tasks that are difficult to determine before data publishing...
November 7, 2016: Journal of Biomedical Informatics
Chuyang Ke, Yan Jin, Heather Evans, Bill Lober, Xiaoning Qian, Ji Liu, Shuai Huang
Surgical Site Infection (SSI) is a national priority in healthcare research. Much research attention has been attracted to develop better SSI risk prediction models. However, most of the existing SSI risk prediction models are built on static risk factors such as comorbidities and operative factors. In this paper, we investigate the use of the dynamic wound data for SSI risk prediction. There have been emerging mobile health (mHealth) tools that can closely monitor the patients and generate continuous measurements of many wound-related variables and other evolving clinical variables...
November 4, 2016: Journal of Biomedical Informatics
Don Roosan, Charlene Weir, Matthew Samore, Makoto Jones, Mumtahena Rahman, Gregory J Stoddard, Guilherme Del Fiol
BACKGROUND: Understanding complexity in healthcare has the potential to reduce decision and treatment uncertainty. Therefore, identifying both patient and task complexity may offer better task allocation and design recommendation for next-generation health information technology system design. OBJECTIVE: To identify the specific complexity-contributing factors in the infectious disease domain and the relationship with the complexity perceived by clinicians. METHOD: We observed and audio recorded the clinical rounds of three infectious disease teams...
November 3, 2016: Journal of Biomedical Informatics
Samah Fodeh, Qing Zeng
No abstract text is available yet for this article.
September 23, 2016: Journal of Biomedical Informatics
Luís Pinho-Costa, Kenneth Yakubu, Kyle Hoedebecke, Liliana Laranjo, Christofer Patrick Reichel, Maria Del C Colon-Gonzalez, Ana Luísa Neves, Hassna Errami
PURPOSE: Create an index of global reach for healthcare hashtags and tweeters therein, filterable by topic of interest. MATERIALS AND METHODS: For this proof-of-concept study we focused on the field of Primary Care and Family Medicine. Six hashtags were selected based on their importance, from the ones included in the 'Healthcare Hashtag Project'. Hashtag Global Reach (HGR) was calculated using the additive aggregation of five weighted, normalized indicator variables: number of impressions, tweets, tweeters, user locations, and user languages...
September 16, 2016: Journal of Biomedical Informatics
Thomas G Kannampallil, Joanna Abraham, Vimla L Patel
We propose a methodological framework for evaluating clinical cognitive activities in complex real-world environments that provides a guiding framework for characterizing the patterns of activities. This approach, which we refer to as a process-based approach, is particularly relevant to cognitive informatics (CI) research-an interdisciplinary domain utilizing cognitive approaches in the study of computing systems and applications-as it provides new ways for understanding human information processing, interactions, and behaviors...
December 2016: Journal of Biomedical Informatics
Sonia Valladares-Rodríguez, Roberto Pérez-Rodríguez, Luis Anido-Rifón, Manuel Fernández-Iglesias
BACKGROUND: The dramatic technological advances witnessed in recent years have resulted in a great opportunity for changing the way neuropsychological evaluations may be performed in clinical practice. Particularly, serious games have been posed as the cornerstone of this still incipient paradigm-shift, as they have characteristics that make them especially advantageous in trying to overcome limitations associated with traditional pen-and-paper based neuropsychological tests: they can be easily administered and they can feature complex environments for the evaluation of neuropsychological constructs that are difficult to evaluate through traditional tests...
December 2016: Journal of Biomedical Informatics
Andres Duque, Juan Martinez-Romo, Lourdes Araujo
Ambiguity in the biomedical domain represents a major issue when performing Natural Language Processing tasks over the huge amount of available information in the field. For this reason, Word Sense Disambiguation is critical for achieving accurate systems able to tackle complex tasks such as information extraction, summarization or document classification. In this work we explore whether multilinguality can help to solve the problem of ambiguity, and the conditions required for a system to improve the results obtained by monolingual approaches...
December 2016: Journal of Biomedical Informatics
Wenxin Ning, Ming Yu, Dehua Kong
BACKGROUND: Semantic similarity estimation significantly promotes the understanding of natural language resources and supports medical decision making. Previous studies have investigated semantic similarity and relatedness estimation between biomedical terms through resources in English, such as SNOMED-CT or UMLS. However, very limited studies focused on the Chinese language, and technology on natural language processing and text mining of medical documents in China is urgently needed...
December 2016: Journal of Biomedical Informatics
Wade L Schulz, Brent G Nelson, Donn K Felker, Thomas J S Durant, Richard Torres
While the adoption of next generation sequencing has rapidly expanded, the informatics infrastructure used to manage the data generated by this technology has not kept pace. Historically, relational databases have provided much of the framework for data storage and retrieval. Newer technologies based on NoSQL architectures may provide significant advantages in storage and query efficiency, thereby reducing the cost of data management. But their relative advantage when applied to biomedical data sets, such as genetic data, has not been characterized...
December 2016: Journal of Biomedical Informatics
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