📄 Category

health informatics

127 papers

Health informatics sits at the vibrant intersection of medicine, data science, and technology, transforming how we store, analyze, and utilize health information. This rapidly evolving field empowers clinicians and researchers to uncover patterns in patient data, improve diagnostic accuracy, and personalize treatment plans without getting lost in complex databases. By turning raw medical records into actionable insights, these innovations are reshaping the future of healthcare delivery and population health management.

At Gist.Science, we bridge the gap between cutting-edge research and public understanding by curating the latest preprints from medRxiv specifically within this domain. Our team processes every new submission in this category, providing both accessible plain-language explanations and detailed technical summaries to ensure the science is clear for everyone, from policymakers to curious readers. Below are the latest papers in health informatics, freshly distilled and ready for you to explore.

Fully Automated Systematic Review Generation via Large Language Models: Quality Assessment and Implications for Scientific Publishing

This study demonstrates that a fully automated pipeline using large language models can generate systematic reviews with citation accuracy and expert-rated quality surpassing human-authored counterparts, while simultaneously revealing critical limitations in information breadth and the urgent need for new verification standards and AI literacy in scientific publishing.

McLaughlin, L., Walz, M. S., Arries, C.2026-02-23📄 health informatics

Machine Learning Analysis of User Sentiments in Tinnitus Management Apps

This study utilizes a graph neural network-based sentiment analysis model on over 340,000 app store reviews to identify that while therapeutic features like sound masking and sleep support drive positive user sentiment, issues regarding pricing, advertisements, and technical stability remain key areas for improvement in tinnitus management apps.

Yousaf, M. N., Anwar, M. N., Naveed, N., Haider, U.2026-02-22📄 health informatics

Clinicians' Rationale for Editing Ambient AI-Drafted Clinical Notes: Persistent Challenges and Implications for Improvement

This study of 30 clinicians reveals that edits to ambient AI-drafted clinical notes are primarily driven by the need to correct transcription errors, ensure clinical accuracy, mitigate liability risks, and meet billing standards, highlighting the necessity for improved AI customization, integration, and institutional support to enhance human-AI collaboration.

Guo, Y., Hu, D., Yang, Z., Chow, E., Tam, S., Perret, D., Pandita, D., Zheng, K.2026-02-22📄 health informatics

Automation of Systematic Reviews with Large Language Models

This study validates "otto-SR," a large language model-based workflow that demonstrates high performance in automating article screening, data extraction, and risk of bias assessment, thereby enabling the rapid and reliable reproduction and updating of systematic reviews.

Cao, C., Arora, R., Cento, P., Budak, A., Manta, K., Farahani, E., Cecere, M., Selemon, A., Sang, J., Gong, L. X., Kloosterman, R., Jiang, S., Saleh, R., Margalik, D., Lin, J., Jomy, J., Xie, J., Chen (…)2026-02-18📄 health informatics

Understanding Comorbidities in Hypermobile Ehlers-Danlos Syndrome: Could a Viral Infection Unmask the Disorder?

Analysis of over 19 million US patient records reveals that individuals with hypermobile Ehlers-Danlos Syndrome face a significantly elevated risk of developing Long COVID, particularly when overlapping with autonomic or immune dysregulation, and suggests that viral infections may often unmask previously undiagnosed cases of the disorder.

Pearson, M. L., Laraway, B. J., Elias, E. R., Bilousova, G., Haendel, M. A.2026-02-17📄 health informatics

Comparing AI and Human Coding of NIH Grant Abstracts to Identify Innovations in Opioid Addiction Treatment

This study demonstrates that when carefully prompted, ChatGPT-4.0 outperforms human coders in generating high-quality, detailed, and complete descriptions of innovations within NIH grant abstracts focused on opioid addiction treatment.

Alkhatib, S. A., Jiwa, N., Judd, D., Luningham, J. M., Sawyer-Morris, G., Ulukaya, M., Molfenter, T., Taxman, F. S., Walters, S. T.2026-02-17📄 health informatics

Sino-US-DrugQA: A Benchmark for Evaluating Large Language Models in Cross-Jurisdictional Pharmaceutical Regulation

This paper introduces Sino-US-DrugQA, a bilingual benchmark dataset of 11,871 questions derived from US and Chinese pharmaceutical regulations, which reveals that while current large language models perform well on monolingual regulatory queries, they face significant challenges in cross-jurisdictional comparative reasoning, necessitating expert oversight for high-stakes compliance applications.

Chen, Z., Fu, X., Lu, W.2026-02-17📄 health informatics

Outcome Risk Modeling for Disability-Free Longevity: Comparison of Random Forest and Random Survival Forest Methods

In a study using ASPREE trial data, Random Survival Forests (RSF) demonstrated comparable discrimination and calibration to standard Random Forests (RF) for predicting disability-free longevity, suggesting that RSF does not always offer superior predictive accuracy over RF for time-to-event outcomes.

Vanghelof, J. C., Tzimas, G., Du, L., Tchoua, R., Shah, R. C.2026-02-17📄 health informatics