Corrigendum to: Evaluating a digital sepsis alert in a London multisite hospital network: a natural experiment using electronic health record data.
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DOI: 10.1093/jamia/ocz219
Author(s):
DOI: 10.1093/jamia/ocz219
The purpose of this study was to understand the ethical, legal, and social issues described by parents of children with known or suspected genetic conditions that cause intellectual and developmental disabilities regarding research use of their child's electronic health record (EHR).
Author(s): Andrews, Sara M, Raspa, Melissa, Edwards, Anne, Moultrie, Rebecca, Turner-Brown, Lauren, Wagner, Laura, Alvarez Rivas, Alexandra, Frisch, Mary Katherine, Wheeler, Anne C
DOI: 10.1093/jamia/ocz208
Scientific commentaries are expected to play an important role in evidence appraisal, but it is unknown whether this expectation has been fulfilled. This study aims to better understand the role of scientific commentary in evidence appraisal. We queried PubMed for all clinical research articles with accompanying comments and extracted corresponding metadata. Five percent of clinical research studies (N = 130 629) received postpublication comments (N = 171 556), resulting in 178 882 comment-article pairings, with 90% published [...]
Author(s): Rogers, James R, Mills, Hollis, Grossman, Lisa V, Goldstein, Andrew, Weng, Chunhua
DOI: 10.1093/jamia/ocz209
To identify predictors of prediabetes using feature selection and machine learning on a nationally representative sample of the US population.
Author(s): De Silva, Kushan, Jönsson, Daniel, Demmer, Ryan T
DOI: 10.1093/jamia/ocz204
Clinical interventions and death in the intensive care unit (ICU) depend on complex patterns in patients' longitudinal data. We aim to anticipate these events earlier and more consistently so that staff can consider preemptive action.
Author(s): Catling, Finneas J R, Wolff, Anthony H
DOI: 10.1093/jamia/ocz205
Development of systematic approaches for understanding and assessing data quality is becoming increasingly important as the volume and utilization of health data steadily increases. In this study, a taxonomy of data defects was developed and utilized when automatically detecting defects to assess Medicaid data quality maintained by one of the states in the United States.
Author(s): Zhang, Yili, Koru, Güneş
DOI: 10.1093/jamia/ocz201
The study sought to assess, for children in one large health system, (1) characteristics of active users of the patient portal (≥1 use in prior 12 months), (2) portal use by adolescents, and (3) variations in pediatric patient portal use.
Author(s): Szilagyi, Peter G, Valderrama, Rebecca, Vangala, Sitaram, Albertin, Christina, Okikawa, David, Sloyan, Michael, Lopez, Nathalie, Lerner, Carlos F
DOI: 10.1093/jamia/ocz203
We propose a one-shot, privacy-preserving distributed algorithm to perform logistic regression (ODAL) across multiple clinical sites.
Author(s): Duan, Rui, Boland, Mary Regina, Liu, Zixuan, Liu, Yue, Chang, Howard H, Xu, Hua, Chu, Haitao, Schmid, Christopher H, Forrest, Christopher B, Holmes, John H, Schuemie, Martijn J, Berlin, Jesse A, Moore, Jason H, Chen, Yong
DOI: 10.1093/jamia/ocz199
This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the clinical domain, providing quantitative analysis to answer 3 research questions concerning methods, scope, and context of current research.
Author(s): Wu, Stephen, Roberts, Kirk, Datta, Surabhi, Du, Jingcheng, Ji, Zongcheng, Si, Yuqi, Soni, Sarvesh, Wang, Qiong, Wei, Qiang, Xiang, Yang, Zhao, Bo, Xu, Hua
DOI: 10.1093/jamia/ocz200
Survival analysis is the cornerstone of many healthcare applications in which the "survival" probability (eg, time free from a certain disease, time to death) of a group of patients is computed to guide clinical decisions. It is widely used in biomedical research and healthcare applications. However, frequent sharing of exact survival curves may reveal information about the individual patients, as an adversary may infer the presence of a person of [...]
Author(s): Bonomi, Luca, Jiang, Xiaoqian, Ohno-Machado, Lucila
DOI: 10.1093/jamia/ocz195