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Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study.
J Med Internet Res
January 2025
Vibrent Health, Inc, Fairfax, VA, United States.
Background: Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used.
Objective: We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health's (NIH) All of Us Research Program (AOU).
With big data comes big responsibility: Strategies for utilizing aggregated, standardized, de-identified electronic health record data for research.
Clin Transl Sci
January 2025
The Center for Clinical Informatics Research and Education, The MetroHealth System, Cleveland, Ohio, USA.
Electronic health records (EHRs), though they are maintained and utilized for clinical and billing purposes, may provide a wealth of information for research. Currently, sources are available that offer insight into the health histories of well over a quarter of a billion people. Their use, however, is fraught with hazards, including introduction or reinforcement of biases, clarity of disease definitions, protection of patient privacy, definitions of covariates or confounders, accuracy of medication usage compared with prescriptions, the need to introduce other data sources such as vaccination or death records and the ensuing potential for inaccuracy, duplicative records, and understanding and interpreting the outcomes of data queries.
View Article and Find Full Text PDFInclusive AI for radiology: Optimising ChatGPT-4 with advanced prompt engineering.
Clin Imaging
February 2025
Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India.
This letter responds to the article "Encouragement vs. liability: How prompt engineering influences ChatGPT-4's radiology exam performance," offering additional perspectives on optimising ChatGPT-4 for Radiology applications. While the study highlights the significance of prompt engineering, we suggest that addressing additional key challenges such as age-related diagnostic needs, socio-economic diversity, data security, and liability concerns is essential for responsible AI integration.
View Article and Find Full Text PDFNot the Models You Are Looking For: Traditional ML Outperforms LLMs in Clinical Prediction Tasks.
medRxiv
December 2024
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Objectives: To determine the extent to which current Large Language Models (LLMs) can serve as substitutes for traditional machine learning (ML) as clinical predictors using data from electronic health records (EHRs), we investigated various factors that can impact their adoption, including overall performance, calibration, fairness, and resilience to privacy protections that reduce data fidelity.
Materials And Methods: We evaluated GPT-3.5, GPT-4, and ML (as gradient-boosting trees) on clinical prediction tasks in EHR data from Vanderbilt University Medical Center and MIMIC IV.
B-UMCS: Blockchain-enabled Unified Medical Consultancy Service.
PLoS One
December 2024
Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh, Saudi Arabia.
The advent of blockchain technology within the healthcare domain has signified a paradigm shift, transitioning from an emerging trend to an essential infrastructure component that ensures decentralization, transparency, integrity, and persistent availability. Despite its potential, the healthcare sector has not fully capitalized on the vast array of benefits blockchain technology offers. Most existing works utilized blockchain technology within a specific healthcare entity's services but not among several healthcare organizations.
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