JMIR medical informatics
Papers 925
1 page of 93 pages (925 results)
#1Meng Ji (USYD: University of Sydney)H-Index: 5
#2Pierrette Bouillon (University of Geneva)H-Index: 16
Background: Linguistic accessibility has an important impact on the reception and utilization of translated health resources among multicultural and multilingual populations. Linguistic understandability of health translation has been understudied. Objective: Our study aimed to develop novel machine learning models for the study of the linguistic accessibility of health translations comparing Chinese translations of the World Health Organization health materials with original Chinese health reso...
#3Yong Chul Kim (New Generation University College)H-Index: 20
#4Dong Ki Kim (New Generation University College)H-Index: 29
Last. Seung Seok Han (New Generation University College)H-Index: 17
view all 8 authors...
Background: Precise prediction of contrast media–induced acute kidney injury (CIAKI) is an important issue because of its relationship with poor outcomes. Objective: Herein, we examined whether a deep learning algorithm could predict the risk of intravenous CIAKI better than other machine learning and logistic regression models in patients undergoing computed tomography (CT). Methods: A total of 14,185 patients who were administered intravenous contrast media for CT at the preventive and monitor...
#1Raghav Ramachandran (APL: Johns Hopkins University Applied Physics Laboratory)
#2Michael J. McShea (APL: Johns Hopkins University Applied Physics Laboratory)
Last. Hadi Kharrazi (Johns Hopkins University)H-Index: 22
view all 7 authors...
BACKGROUND A high proportion of healthcare services are persistently utilized by a small subpopulation of patients. To improve clinical outcomes while reducing cost and utilization, population health management programs often provide targeted interventions to patients who may become persistent high users/utilizers (PHUs). Enhanced prediction and management of PHUs can improve healthcare system efficiencies and improve the overall quality of patient care. OBJECTIVE To detect key classes of diseas...
#1Sooho Choe (Yonsei University)
#2Eunjeong Park (Yonsei University)H-Index: 13
Last. Jeongmin Kim (Yonsei University)H-Index: 16
view all 8 authors...
BACKGROUND Intraoperative hypotension has an adverse impact on postoperative outcomes. However, it is difficult to predict and treat intraoperative hypotension in advance according to individual clinical parameters. OBJECTIVE The aim of this study was to develop a prediction model to forecast 5-minute intraoperative hypotension based on the weighted average ensemble of individual neural networks, utilizing the biosignals recorded during noncardiac surgery. METHODS In this retrospective observati...
#1Abeed Sarker (Emory University)H-Index: 20
#2Mohammed Ali Al-Garadi (Emory University)H-Index: 20
Last. Greg S. Martin (Emory University)H-Index: 63
view all 6 authors...
The capabilities of natural language processing (NLP) methods have expanded significantly in recent years, and progress has been particularly driven by advances in data science and machine learning. However, NLP is still largely underused in patient-oriented clinical research and care (POCRC). A key reason behind this is that clinical NLP methods are typically developed, optimized, and evaluated with narrowly focused data sets and tasks (eg, those for the detection of specific symptoms in free t...
BACKGROUND: Within the context of the COVID-19 pandemic, this article suggests a data science strategy for analyzing global research on coronaviruses. The application of reproducible research principles founded on text-as-data, open science, the dissemination of scientific data, and easy access to scientific production may aid public health in the fight against the virus. OBJECTIVE: The primary goal of this article is to use global research on coronaviruses to identify critical elements that can...
#1Umar Ruhi (U of O: University of Ottawa)H-Index: 6
#2Armin Majedi (U of O: University of Ottawa)
Last. Ritesh Chugh (Central Queensland University)H-Index: 11
view all 3 authors...
BACKGROUND Increasingly popular in the health care domain, electronic personal health records (PHRs) have the potential to foster engagement toward improving health outcomes, achieving efficiencies in care, and reducing costs. Despite the touted benefits of PHRs, their uptake is lackluster, with low adoption rates. OBJECTIVE This paper reports findings from an empirical investigation of the sociotechnical factors affecting the adoption of PHRs. METHODS A research model comprising personal and te...
#1Dongyup Shin (Yonsei University)
#2Hye Jin KamH-Index: 7
Last. Ha-young Kim (Yonsei University)H-Index: 13
view all 4 authors...
Background: In the case of Korean institutions and enterprises that collect nonstandardized and nonunified formats of electronic medical examination results from multiple medical institutions, a group of experienced nurses who can understand the results and related contexts initially classified the reports manually. The classification guidelines were established by years of workers’ clinical experiences and there were attempts to automate the classification work. However, there have been problem...
#1Meng Ji (USYD: University of Sydney)H-Index: 5
#2Yanmeng Liu (USYD: University of Sydney)
Last. Tianyong Hao (SCNU: South China Normal University)H-Index: 18
view all 3 authors...
#1Vishnu Mohan (OHSU: Oregon Health & Science University)H-Index: 13
#2Cort Garrison (OHSU: Oregon Health & Science University)
Last. Jeffrey A. Gold (OHSU: Oregon Health & Science University)H-Index: 25
view all 3 authors...
Physician burnout in the United States has been growing at an alarming rate, and health care organizations are beginning to invest significant resources in combating this phenomenon. Although the causes for burnout are multifactorial, a key issue that affects physicians is that they spend a significant proportion of their time interacting with their electronic health record (EHR) system, primarily because of the need to sift through increasing amounts of patient data, coupled with a significant ...
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Machine learning
Data mining
Health informatics
Health care
Medical record
Natural language processing
Computer science
Medical emergency
Receiver operating characteristic