Journal of Healthcare Informatics Research

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NeighBERT: Medical Entity Linking Using Relation-Induced Dense Retrieval
Journal of Healthcare Informatics Research - - Trang 1-17 - 2024
Ayush Singh, Saranya Krishnamoorthy, John E. Ortega
One of the common tasks in clinical natural language processing is medical entity linking (MEL) which involves mention detection followed by linking the mention to an entity in a knowledge base. One reason that MEL has not been solved is due to a problem that occurs in language where ambiguous texts can be resolved to several named entities. This problem is exacerbated when processing the text fou... hiện toàn bộ
The Case for Computational Health Science
Journal of Healthcare Informatics Research - Tập 2 Số 1 - Trang 99-110 - 2018
Barnes, M., Hanson, C., Giraud-Carrier, C.
In this introductory paper, we begin by making the case for Computational Health Science, which we define as the interdisciplinary efforts of health scientists, computer scientists, engineers, psychologists, and other social scientists, to conduct innovative research that will inform future practice directed at changing health behavior through improved communication, networking, and social capital... hiện toàn bộ
Applying Bidirectional Transformations to the Design of Interoperable EMR Systems
Journal of Healthcare Informatics Research - Tập 4 - Trang 138-150 - 2020
Jens H. Weber, Jeremy Ho
Interoperability between heterogeneous health information systems has remained an elusive goal despite decades of exchange standards development and implementation initiatives. Empirical studies have shown that in many cases, implemented interoperability interfaces fail to function correctly. Unfortunately, the health informatics literature provides little guidance on how to best design and assure... hiện toàn bộ
System-Subsystem Dependency Network for Integrating Multicomponent Data and Its Application to Health Sciences
Journal of Healthcare Informatics Research - Tập 1 - Trang 139-156 - 2017
Edward H. Ip, Shyh-Huei Chen, W. Jack Rejeski
With the ever-increasing demand of collecting and analyzing a large volume of data collected from different sources, computational models and methods—ones that allow for the integration of data sets to help understand a phenomenon from a broad, comprehensive systems perspective—are called for. Two features are commonly observed in large and complex systems. First, a system is made up of multiple s... hiện toàn bộ
Imputation of Missing Data in Electronic Health Records Based on Patients’ Similarities
Journal of Healthcare Informatics Research - Tập 4 - Trang 295-307 - 2020
Ali Jazayeri, Ou Stella Liang, Christopher C. Yang
Using electronic health records (EHR) as the source of data for mining and analysis of different health conditions has become an increasingly common approach. However, due to irregular observation times and other uncertainties inherent in medical settings, the EHR data sets suffer from a large number of missing values. Most of the traditional data mining and machine learning approaches are designe... hiện toàn bộ
Salience of Medical Concepts of Inside Clinical Texts and Outside Medical Records for Referred Cardiovascular Patients
Journal of Healthcare Informatics Research - Tập 3 Số 2 - Trang 200-219 - 2019
Sungrim Moon, Sijia Liu, David Chen, Yanshan Wang, Douglas L. Wood, Rajeev Chaudhry, Hongfang Liu, Paul Kingsbury
ALeRT-COVID: Attentive Lockdown-awaRe Transfer Learning for Predicting COVID-19 Pandemics in Different Countries
Journal of Healthcare Informatics Research - Tập 5 - Trang 98-113 - 2021
Yingxue Li, Wenxiao Jia, Junmei Wang, Jianying Guo, Qin Liu, Xiang Li, Guotong Xie, Fei Wang
Countries across the world are in different stages of COVID-19 trajectory, among which many have implemented lockdown measures to prevent its spread. Although the lockdown is effective in such prevention, it may put the economy into a depression. Predicting the epidemic progression with the government switching the lockdown on or off is critical. We propose a transfer learning approach called ALeR... hiện toàn bộ
A Machine Learning Framework for Assessing the Risk of Venous Thromboembolism in Patients Undergoing Hip or Knee Replacement
Journal of Healthcare Informatics Research - Tập 6 - Trang 423-441 - 2022
Elham Rasouli Dezfouli, Dursun Delen, Huimin Zhao, Behrooz Davazdahemami
Venous thromboembolism (VTE) is a well-recognized complication that is prevalent in patients undergoing major orthopedic surgery (e.g., total hip arthroplasty and total knee arthroplasty). For years, to identify patients at high risk of developing VTE, physicians have relied on traditional risk scoring systems, which are too simplistic to capture the risk level accurately. In this paper, we propos... hiện toàn bộ
Prompt Tuning in Biomedical Relation Extraction
Journal of Healthcare Informatics Research - - 2024
Jianping He, Fang Li, Jianfu Li, Xinyue Hu, Yi Nian, Yang Xiang, Jingqi Wang, Qiang Wei, Yiming Li, Hua Xu, Cui Tao
Biomedical relation extraction (RE) is critical in constructing high-quality knowledge graphs and databases as well as supporting many downstream text mining applications. This paper explores prompt tuning on biomedical RE and its few-shot scenarios, aiming to propose a simple yet effective model for this specific task. Prompt tuning reformulates natural language processing (NLP) downstream tasks ... hiện toàn bộ
Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview
Journal of Healthcare Informatics Research - Tập 8 Số 1 - Trang 121-139 - 2024
Ban Al-Sahab, Alan Leviton, Tobias Loddenkemper, Nigel Paneth, Bo Zhang
Tổng số: 109   
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