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Journal of Biomedical Informatics

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https://www.readbyqxmd.com/read/28435015/using-classification-models-for-the-generation-of-disease-specific-medications-from-biomedical-literature-and-clinical-data-repository
#1
Liqin Wang, Peter J Haug, Guilherme Del Fiol
OBJECTIVE: Mining disease-specific associations from existing knowledge resources can be useful for building disease-specific ontologies and supporting knowledge-based applications. Many association mining techniques have been exploited. However, the challenge remains when those extracted associations contained much noise. It is unreliable to determine the relevance of the association by simply setting up arbitrary cut-off points on multiple scores of relevance; and it would be expensive to ask human experts to manually review a large number of associations...
April 20, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28433826/data-summarization-method-for-chronic-disease-tracking
#2
Dejan Aleksić, Petar Rajković, Dušan Vučković, Dragan Janković, Aleksandar Milenković
OBJECTIVES: Bearing in mind the rising prevalence of chronic medical conditions, the chronic disease management is one of the key features required by medical information systems used in primary healthcare. Our research group paid a particular attention to this specific area by offering a set of custom data collection forms and reports in order to improve medical professionals' daily routine. The main idea was to provide an overview of history for chronic diseases, which, as it seems, had not been properly supported in previous administrative workflows...
April 19, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28433825/a-distributed-framework-for-health-information-exchange-using-smartphone-technologies
#3
Mohamed Abdulnabi, Ahmed Al-Haiqi, Mlm Kiah, A A Zaidan, B B Zaidan, Muzammil Hussein
Nationwide health information exchange (NHIE) continues to be a persistent concern for government agencies, despite the many efforts and the conceived benefits of sharing patient data among healthcare providers. Difficulties in ensuring global connectivity, interoperability, and concerns on security have always hampered the government from successfully deploying NHIE. By looking at NHIE from a fresh perspective and bearing in mind the pervasiveness and power of modern mobile platforms, this paper proposes a new approach to NHIE that builds on the notion of consumer-mediated HIE, albeit without the focus on central health record banks...
April 19, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28428140/automated-annotation-and-classification-of-bi-rads-assessment-from-radiology-reports
#4
Sergio M Castro, Eugene Tseytlin, Olga Medvedeva, Kevin Mitchell, Shyam Visweswaran, Tanja Bekhuis, Rebecca S Jacobson
The Breast Imaging Reporting and Data System (BI-RADS) was developed to reduce variation in the descriptions of findings. Manual analysis of breast radiology report data is challenging but is necessary for clinical and healthcare quality assurance activities. The objective of this study is to develop a natural language processing (NLP) system for automated BI-RADS categories extraction from breast radiology reports. We evaluated an existing rule-based NLP algorithm, and then we developed and evaluated our own method using a supervised machine learning approach...
April 17, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28410983/toward-better-public-health-reporting-using-existing-off-the-shelf-approaches-the-value-of-medical-dictionaries-in-automated-cancer-detection-using-plaintext-medical-data
#5
Suranga N Kasthurirathne, Brian E Dixon, Judy Gichoya, Huiping Xu, Yuni Xia, Burke Mamlin, Shaun J Grannis
OBJECTIVES: Existing approaches to derive decision models from plaintext clinical data frequently depend on medical dictionaries as the sources of potential features. Prior research suggests that decision models developed using non-dictionary based feature sourcing approaches and "off the shelf" tools could predict cancer with performance metrics between 80%-90%. We sought to compare non-dictionary based models to models built using features derived from medical dictionaries. MATERIALS AND METHODS: We evaluated the detection of cancer cases from free text pathology reports using decision models built with combinations of dictionary or non-dictionary based feature sourcing approaches, 4 feature subset sizes, and 5 classification algorithms...
April 11, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28410982/ehr-based-phenotyping-bulk-learning-and-evaluation
#6
Po-Hsiang Chiu, George Hripcsak
In data-driven phenotyping, a core computational task is to identify medical concepts and their variations from sources of electronic health records (EHR) to stratify phenotypic cohorts. A conventional analytic framework for phenotyping largely uses a manual knowledge engineering approach or a supervised learning approach where clinical cases are represented by variables encompassing diagnoses, medicinal treatments and laboratory tests, among others. In such a framework, tasks associated with feature engineering and data annotation remain a tedious and expensive exercise, resulting in poor scalability...
April 11, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28410981/predicting-healthcare-trajectories-from-medical-records-a-deep-learning-approach
#7
Trang Pham, Truyen Tran, Dinh Phung, Svetha Venkatesh
Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, stored in electronic medical records are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors and models patient health state trajectories by the memory of historical records...
April 11, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28404537/building-a-comprehensive-syntactic-and-semantic-corpus-of-chinese-clinical-texts
#8
Bin He, Bin Dong, Yi Guan, Jinfeng Yang, Zhipeng Jiang, Qiubin Yu, Jianyi Cheng, Chunyan Qu
OBJECTIVE: To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baselines for research on Chinese texts in the clinical domain. MATERIALS AND METHODS: An iterative annotation method was proposed to train annotators and to develop annotation guidelines. Then, by using annotation quality assurance measures, a comprehensive corpus was built, containing annotations of part-of-speech (POS) tags, syntactic tags, entities, assertions, and relations...
April 9, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28400313/the-emouverecherche-application-competes-with-research-devices-to-evaluate-energy-expenditure-physical-activity-and-still-time-in-free-living-conditions
#9
Romain Guidoux, Martine Duclos, Gérard Fleury, Philippe Lacomme, Nicolas Lamaudière, Damien Saboul, Libo Ren, Sylvie Rousset
The proliferation of smartphones is creating new opportunities to monitor and interact with human subjects in free-living conditions since smartphones are familiar to large segments of the population and facilitate data collection, transmission and analysis. From accelerometry data collected by smartphones, the present work aims to estimate time spent in different activity categories and the energy expenditure in free-living conditions. Our research encompasses the definition of an energy-saving function (Pred(EE)) considering four physical categories of activities (still, light, moderate and vigorous), their duration and metabolic cost (MET)...
April 8, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28400312/assigning-clinical-codes-with-data-driven-concept-representation-on-dutch-clinical-free-text
#10
Elyne Scheurwegs, Kim Luyckx, Léon Luyten, Bart Goethals, Walter Daelemans
Clinical codes are used for public reporting purposes, are fundamental to determining public financing for hospitals, and form the basis for reimbursement claims to insurance providers. They are assigned to a patient stay to reflect the diagnosis and performed procedures during that stay. This paper aims to enrich algorithms for automated clinical coding by taking a data-driven approach and by using unsupervised and semi-supervised techniques for the extraction of multi-word expressions that convey a generalisable medical meaning (referred to as concepts)...
April 8, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28389234/crowd-control-effectively-utilizing-unscreened-crowd-workers-for-biomedical-data-annotation
#11
Anne Cocos, Ting Qian, Chris Callison-Burch, Aaron J Masino
Annotating unstructured texts in Electronic Health Records data is usually a necessary step for conducting machine learning research on such datasets. Manual annotation by domain experts provides data of the best quality, but has become increasingly impractical given the rapid increase in the volume of EHR data. In this article, we examine the effectiveness of crowdsourcing with unscreened online workers as an alternative for transforming unstructured texts in EHRs into annotated data that are directly usable in supervised learning models...
April 4, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28389233/zk-drugresist-2-0-a-textminer-to-extract-semantic-relations-of-drug-resistance-from-pubmed
#12
Zoya Khalid, Osman Ugur Sezerman
Extracting useful knowledge from an unstructured textual data is a challenging task for biologists, since biomedical literature is growing exponentially on a daily basis. Building an automated method for such tasks is gaining much attention of researchers. ZK DrugResist is an online tool that automatically extracts mutations and expression changes associated with drug resistance from PubMed. In this study we have extended our tool to include semantic relations extracted from biomedical text covering drug resistance and established a server including both of these features...
April 4, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28366789/envisioning-the-future-of-big-data-biomedicine
#13
Alex A T Bui, John Darrell Van Horn
In our era of digital biomedicine, data take many forms, from "omics" to imaging, mobile health (mHealth), and electronic health records (EHRs). With the availability of more efficient digital collection methods, scientists in many domains now find themselves confronting ever larger sets of data and trying to make sense of it all (1-4). Indeed, data which used to be considered large now seems small as the amount of data now being collected in a single day by an investigator can surpass what might have been generated over his/her career even a decade ago (e...
March 30, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28359728/enriching-consumer-health-vocabulary-through-mining-a-social-q-a-site-a-similarity-based-approach
#14
Zhe He, Zhiwei Chen, Sanghee Oh, Jinghui Hou, Jiang Bian
The widely known vocabulary gap between health consumers and healthcare professionals hinders information seeking and health dialogue of consumers on end-user health applications. The Open Access and Collaborative Consumer Health Vocabulary (OAC CHV), which contains health-related terms used by lay consumers, has been created to bridge such a gap. Specifically, the OAC CHV facilitates consumers' health information retrieval by enabling consumer-facing health applications to translate between professional language and consumer friendly language...
March 27, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28347856/a-multidisciplinary-approach-to-designing-and-evaluating-electronic-medical-record-portal-messages-that-support-patient-self-care
#15
Daniel Morrow, Mark Hasegawa-Johnson, Thomas Huang, William Schuh, Renato Ferreira Leitão Azevedo, Kuangxiao Gu, Yang Zhang, Bidisha Roy, Rocio Garcia-Retamero
We describe a project intended to improve the use of Electronic Medical Record (EMR) patient portal information by older adults with diverse numeracy and literacy abilities, so that portals can better support patient-centered care. Patient portals are intended to bridge patients and providers by ensuring patients have continuous access to their health information and services. However, they are underutilized, especially by older adults with low health literacy, because they often function more as information repositories than as tools to engage patients...
March 24, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28342946/negait-a-new-parser-for-medical-text-simplification-using-morphological-sentential-and-double-negation
#16
Partha Mukherjee, Gondy Leroy, David Kauchak, Srinidhi Rajanarayanan, Damian Y Romero Diaz, Nicole P Yuan, T Gail Pritchard, Sonia Colina
Many different text features influence text readability and content comprehension. Negation is commonly suggested as one such feature, but few general-purpose tools exist to discover negation and studies of the impact of negation on text readability are rare. In this paper, we introduce a new negation parser (NegAIT) for detecting morphological, sentential, and double negation. We evaluated the parser using a human annotated gold standard containing 500 Wikipedia sentences and achieved 95%, 89% and 67% precision with 100%, 80%, and 67% recall, respectively...
March 22, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28336478/an-extended-protocol-for-usability-validation-of-medical-devices-research-design-and-reference-model
#17
Martin Schmettow, Raphaela Schnittker, Jan Maarten Schraagen
This paper proposes and demonstrates an extended protocol for usability validation testing of medical devices. A review of currently used methods for the usability evaluation of medical devices revealed two main shortcomings. Firstly, the lack of methods to closely trace the interaction sequences and derive performance measures. Secondly, a prevailing focus on cross-sectional validation studies, ignoring the issues of learnability and training. The U.S. Federal Drug and Food Administration's recent proposal for a validation testing protocol for medical devices is then extended to address these shortcomings: (1) a novel process measure 'normative path deviations' is introduced that is useful for both quantitative and qualitative usability studies and (2) a longitudinal, completely within-subject study design is presented that assesses learnability, training effects and allows analysis of diversity of users...
March 21, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28336477/a-novel-semantic-representation-for-eligibility-criteria-in-clinical-trials
#18
Efthymios Chondrogiannis, Vassiliki Andronikou, Anastasios Tagaris, Efstathios Karanastasis, Theodora Varvarigou, Masatsugu Tsuji
Eligibility Criteria (EC) comprise an important part of a clinical study, being determinant of its cost, duration and overall success. Their formal, computer-processable description can significantly improve clinical trial design and conduction by enabling their intelligent processing, replicability and linkability with other data. For EC representation purposes, related standards were investigated, along with published literature. Moreover, a considerable number of clinicaltrials.gov studies was analyzed in collaboration with clinical experts for the determination and classification of parameters of clinical research importance...
March 21, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28323113/longitudinal-analysis-of-discussion-topics-in-an-online-breast-cancer-community-using-convolutional-neural-networks
#19
Shaodian Zhang, Edouard Grave, Elizabeth Sklar, Noémie Elhadad
Identifying topics of discussions in online health communities (OHC) is critical to various information extraction applications, but can be difficult because topics of OHC content are usually heterogeneous and domain-dependent. In this paper, we provide a multi-class schema, an annotated dataset, and supervised classifiers based on convolutional neural network (CNN) and other models for the task of classifying discussion topics. We apply the CNN classifier to the most popular breast cancer online community, and carry out cross-sectional and longitudinal analyses to show topic distributions and topic dynamics throughout members' participation...
March 18, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28323114/physician-activity-during-outpatient-visits-and-subjective-workload
#20
Alan Calvitti, Harry Hochheiser, Shazia Ashfaq, Kristin Bell, Yunan Chen, Robert El Kareh, Mark T Gabuzda, Lin Liu, Sara Mortensen, Braj Pandey, Steven Rick, Richard L Street, Nadir Weibel, Charlene Weir, Zia Agha
We describe methods for capturing and analyzing EHR use and clinical workflow of physicians during outpatient encounters and relating activity to physicians' self-reported workload. We collected temporally-resolved activity data including audio, video, EHR activity, and eye-gaze along with post-visit assessments of workload. These data are then analyzed through a combination of manual content analysis and computational techniques to temporally align streams, providing a range of process measures of EHR usage, clinical workflow, and physician-patient communication...
March 17, 2017: Journal of Biomedical Informatics
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