Information Technology

Advancing FAIR Data Management through AI-Assisted Curation of Morphological Data Matrices

Curation of biological and paleontological datasets is a labor-intensive process that requires standardization and validation to ensure data integrity. In particular, manual curation of datasets is prone to human errors such as typographical errors, inconsistent formatting, and incomplete metadata, which hinder reproducibility and compliance with Findability, Accessibility, Interoperability, and R...

Integrating Genomics into Multimodal EHR Foundation Models

This paper introduces an innovative Electronic Health Record (EHR) foundation model that integrates Polygenic Risk Scores (PRS) as a foundational data modality, moving beyond traditional EHR-only approaches to build more holistic health profiles. Leveraging the extensive and diverse data from the All of Us (AoU) Research Program, this multimodal framework aims to learn complex relationships betwee...

Systematic Survey of Public Datasets for Behavioral Research in Invertebrate Models: Toward FAIR and Standardized Data Sharing

Behavioral datasets for invertebrate model organisms are rapidly expanding alongside automated imaging, tracking, and artificial intelligence (AI) bas...

Machine learning prediction algorithms for 2- , 5- and 10-year risk of Alzheimer’s, Parkinson’s and dementia at age 65: a study using medical records from France and the UK General Practitioners

Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and ne...

Augmenting Fact and Date of Death in Electronic Health Records using Internet Media Sources: A Validation Study from Two Large Healthcare Systems

To evaluate the validity of death ascertainment from publicly available internet media (IM) sources by benchmarking against state and Federal vital st...

Electronic Health Record-Based Prediction Models to Inform Decisions about HIV Pre-exposure Prophylaxis: A Systematic Review

Several clinical prediction models have been developed using electronic health records data to help inform decisions about HIV pre-exposure prophylaxi...

Summarizing Clinical Notes using LLMs for ICU Bounceback and Length-of-Stay Prediction

Recent advances in the Large Language Models (LLMs) provide a promising avenue for retrieving relevant information from clinical notes for accurate ri...

Development and Validation of Natural Language Processing Algorithms in the ENACT National Electronic Health Record Research Network

Electronic health record (EHR) data are a rich and invaluable source of real-world clinical information, enabling detailed insights into patient popul...

Introducing and Evaluating the Patient Report Template for AI-Powered Nursing Handoffs

This study evaluates the effectiveness of the Patient Report Template (PRT) in addressing inefficiencies in nursing workflows related to electronic he...

Computational Phenomapping of Randomized Clinical Trials to Enable Assessment of their Real-world Representativeness and Personalized Inference

Randomized clinical trials (RCTs) define evidence-based medicine, but quantifying their generalizability to real-world patients remains challenging. W...

Large Language Models Struggle to Encode Medical Concepts — A Multilingual Benchmarking and Comparative Analysis

Interoperability in health information systems is crucial for accurate data exchange across environments such as electronic health records, clinical n...

A deep learning model for clinical outcome prediction using longitudinal inpatient electronic health records

Recent advances in deep learning show significant potential in analyzing continuous monitoring electronic health records (EHR) data for clinical outco...

Deep representation learning for clustering longitudinal survival data from electronic health records

Precision medicine requires accurate identification of clinically relevant patient subgroups. Electronic health records provide major opportunities fo...

Profiling and Predicting Faculty Assessment Behavior in Surgical Education

To study and profile the digital assessment behaviors of surgical faculty and residents, and to build a classifier to predict assessment completion, e...

Natural language processing for scalable feature engineering and ultra-high-dimensional confounding adjustment in healthcare database studies

To improve confounding control in healthcare database studies, data-driven algorithms may empirically identify and adjust for large numbers of pre-exp...

Phenotyping Adolescent Endometriosis: Characterizing Symptom Heterogeneity Through Note- and Patient-Level Clustering

Pelvic pain (dysmenorrhea and non-menstrual) is the most common presentation of adolescent endometriosis, but symptoms vary between and within patient...

A Scalable Method for Validated Data Extraction from Electronic Health Records with Large Language Models

Extracting and structuring relevant clinical information from electronic health records (EHRs) remains a challenge due to the heterogeneity of systems...

Identifying and Forecasting Importation and Asymptomatic Spreaders of Multi-drug Resistant Organisms in Hospital Settings

Healthcare-associated infections (HAIs) from multi-drug resistant organisms (MDROs) pose a signif-icant challenge for healthcare systems. Patients can...

Life Events Extraction From Healthcare Notes for Veteran Acute Suicide Prediction

Predictive models of suicide risk have focused on predictors extracted from structured data found in electronic health records (EHR), with limited con...

The role of artificial intelligence in the application of the integrated electronic health records and patient-generated health data

This scoping review aims to identify and understand the role of artificial intelligence in the application of integrated electronic health records (EH...