The Need for Expanded Educational Opportunities in Clinical Informatics for Pediatric Trainees.
Author(s): Yan, Adam P, Yarahuan, Julia, Hron, Jonathan D
DOI: 10.1055/a-2340-7142
Author(s): Yan, Adam P, Yarahuan, Julia, Hron, Jonathan D
DOI: 10.1055/a-2340-7142
Heart failure is a complex clinical syndrome noted on approximately one in eight death certificates in the United States. Vital to reducing complications of heart failure and preventing hospital readmissions is adherence to heart failure self-care routines. Mobile health offers promising opportunities for enhancing self-care behaviors by facilitating tracking and timely reminders.
Author(s): Sohn, Albert, Turner, Anne M, Speier, William, Fonarow, Gregg C, Ong, Michael K, Arnold, Corey W
DOI: 10.1055/a-2273-5278
The aim of this project was to create time-aware, individual-level risk score models for adverse drug events related to multiple sclerosis disease-modifying therapy and to provide interpretable explanations for model prediction behavior.
Author(s): Patterson, Jason, Tatonetti, Nicholas
DOI: 10.1093/jamia/ocae155
To explore the feasibility of validating Dutch concept extraction tools using annotated corpora translated from English, focusing on preserving annotations during translation and addressing the scarcity of non-English annotated clinical corpora.
Author(s): Seinen, Tom M, Kors, Jan A, van Mulligen, Erik M, Rijnbeek, Peter R
DOI: 10.1093/jamia/ocae159
The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the [...]
Author(s): Ren, Yang, Wu, Yuqi, Fan, Jungwei W, Khurana, Aditya, Fu, Sunyang, Wu, Dezhi, Liu, Hongfang, Huang, Ming
DOI: 10.1093/jamia/ocae144
To introduce quantum computing technologies as a tool for biomedical research and highlight future applications within healthcare, focusing on its capabilities, benefits, and limitations.
Author(s): Durant, Thomas J S, Knight, Elizabeth, Nelson, Brent, Dudgeon, Sarah, Lee, Seung J, Walliman, Dominic, Young, Hobart P, Ohno-Machado, Lucila, Schulz, Wade L
DOI: 10.1093/jamia/ocae149
Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal [...]
Author(s): Chowdhury, Shaika, Chen, Yongbin, Li, Pengyang, Rajaganapathy, Sivaraman, Wen, Andrew, Ma, Xiao, Dai, Qiying, Yu, Yue, Fu, Sunyang, Jiang, Xiaoqian, He, Zhe, Sohn, Sunghwan, Liu, Xiaoke, Bielinski, Suzette J, Chamberlain, Alanna M, Cerhan, James R, Zong, Nansu
DOI: 10.1093/jamia/ocae137
Blood product ordering is a complex process and mistakes can harm patients and lead to poor outcomes. Orders and order sets can be designed to help mitigate errors, but major changes in design can unintentionally cause new errors.
Author(s): Thompson, Sarah A, Williams, Herb, Rzewnicki, Daniel, Orenstein, Evan, Carter, Alexis B, Rollins, Margo, Rogers, Beverly, Kandaswamy, Swaminathan
DOI: 10.1055/a-2351-9642
This study aims to investigate the feasibility of using Large Language Models (LLMs) to engage with patients at the time they are drafting a question to their healthcare providers, and generate pertinent follow-up questions that the patient can answer before sending their message, with the goal of ensuring that their healthcare provider receives all the information they need to safely and accurately answer the patient's question, eliminating back-and-forth messaging, and [...]
Author(s): Liu, Siru, Wright, Aileen P, Mccoy, Allison B, Huang, Sean S, Genkins, Julian Z, Peterson, Josh F, Kumah-Crystal, Yaa A, Martinez, William, Carew, Babatunde, Mize, Dara, Steitz, Bryan, Wright, Adam
DOI: 10.1093/jamia/ocae142
Author name incompleteness, referring to only first initial available instead of full first name, is a long-standing problem in MEDLINE and has a negative impact on biomedical literature systems. The purpose of this study is to create an Enhanced Author Names (EAN) dataset for MEDLINE that maximizes the number of complete author names.
Author(s): Zhang, Li, Song, Ningyuan, Gui, Sisi, Wu, Keye, Lu, Wei
DOI: 10.1093/jamia/ocae127