health informatics 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.

📄 health informatics

Predicting Depression and Anxiety Progression in Multiple Sclerosis from Longitudinal Clinical Data Using Machine Learning

This study demonstrates that while gradient boosting models using structured electronic health record data can predict depression and anxiety progression in multiple sclerosis patients, their limited predictive power (R² ≤ 0.28) is dominated by baseline scores reflecting regression to the mean, indicating that richer data sources beyond structured clinical variables are necessary for meaningful individual-level forecasting.

Specht, B., Garbaya, S., Schneider, R., Khadraoui, D., Chavarriaga, R., Tayeb, Z.2026-06-25

📄 health informatics

AI-driven Multimodal Representation Learning for Latent Mediation Structure Discovery of Socioeconomic Disadvantage, Psychosocial Factors, and Cardiometabolic Multimorbidity

This study employs an AI-driven multimodal mediation framework to analyze data from the All of Us Research Program, revealing that psychosocial vulnerability acts as a key latent mediator linking socioeconomic disadvantage to cardiometabolic multimorbidity.

Ma, S., Cao, C.2026-06-23

📄 health informatics

Demographic Calibration Gaps in Breast Cancer Risk Prediction: Introducing the Demographic Calibration Gap Score

This paper introduces the Demographic Calibration Gap Score (DCGS) to demonstrate that standard global calibration methods fail to address systematic prediction errors across racial and gender subgroups in breast cancer risk models, particularly under distributional shifts, thereby highlighting the need for subgroup-specific calibration metrics to prevent biased clinical decisions.

Eniolade, M.2026-06-22

📄 health informatics

Generative Artificial Intelligence in Psychotherapy Practice: A Global Online Survey of Mental Health Professionals' Adoption

A global survey of 766 mental health professionals reveals that over half are already using generative AI tools, primarily for treatment planning and administrative tasks, yet this widespread adoption occurs despite a significant lack of institutional guidance, formal training, and regulatory frameworks.

Blease, C., Hagström, J., Gaab, J., Carey, A., Cipriani, F., Gorman, C., Nascimento, A. F., Fitzgerald, A., Holtz, L. (…)2026-06-22

📄 health informatics

Looked but didn't see: inattentional blindness and yes-bias confabulation in vision-language models

This paper demonstrates that vision-language models exhibit inattentional blindness similar to humans but also display a unique confabulation failure mode, necessitating signal-detection analysis with matched-control baselines to accurately assess their visual perception capabilities.

Raymond, J. D., Hu, P., Solomon, B. D., Duong, D.2026-06-18

📄 health informatics

Mapping Chemical-Gene Interactions for Developmental Lethality and Pregnancy Loss

This study introduces the Chemical-Gene Atlas (CGA), an interactive resource integrating 4,110 chemicals with 928 developmental lethality-associated genes to map exposure-specific vulnerabilities across gestational windows and identify key gene-environment interactions underlying recurrent pregnancy loss.

Bukhari, S. H., Nagasuri, A., Oskotsky, B., Arnaout, L., Minkovski, P., Correia, G. D. S., MacIntyre, D. A., Shaw, G. M. (…)2026-06-16

📄 health informatics

WITHDRAWN: Advancing Breast Cancer-AI Diagnostics: An Explainable Deep Learning Model Using 2D Grayscale Ultrasound Imaging

This manuscript, which proposed an explainable deep learning model for breast cancer diagnosis using 2D grayscale ultrasound, has been withdrawn by the authors due to conflicts of interest and a co-author's disagreement with the methodology.

Abbas, G. H., Rehman, S. U., Bargshady, G.2026-06-16

📄 health informatics

SPIRIT-CONSORT-ELM: Element-Level Assessment of Randomized Controlled Trial Reporting Using Large Language Models

This paper introduces SPIRIT-CONSORT-ELM, a novel framework and dataset that extends existing reporting guidelines to the element level, utilizing a hybrid pipeline of PubMedBERT and generative large language models to automatically assess the completeness and transparency of randomized controlled trial reports with high accuracy.

Jiang, L., Ying, X., Brown, A. W., Lan, M., Song, W., Menke, J., Vorland, C., Mayo-Wilson, E., Kilicoglu, H.2026-06-15

📄 health informatics

Unveiling the Awareness of Private Health Insurance Coverage among Healthcare Professionals in Freetown, Sierra Leone: Insights Extracted from Their Perspectives.

This cross-sectional study of healthcare professionals in Freetown, Sierra Leone, reveals a low prevalence of private health insurance coverage despite high enrollment willingness, with no significant demographic or socioeconomic factors identified as determinants, highlighting the need to address unexamined barriers like cost and accessibility to advance Universal Health Coverage in the region.

Gary, L. P., Kamara, A. N., Jimmy, A. I., Lebbie, A. P.2026-06-15

📄 health informatics

Validity and Limitations of the Empatica E4 Wristband for Autonomic and Thermoregulatory Sleep Monitoring Against Concurrent Polysomnography: A Wearanize+ Dataset Study

This study validates the Empatica E4 wristband's utility for sleep research by analyzing the Wearanize+ dataset, confirming its accuracy in tracking heart rate and skin temperature across sleep stages while identifying specific limitations in electrodermal activity measurements due to wrist sweat accumulation.

Parry, Y. D., Briganti, G.2026-06-11

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