Information Technology

Robotic telepresence versus standardly supervised stroke alert team assessments.

BACKGROUND: Telemedicine has created access to emergency stroke care for patients in all communities, regardless of geography. We hypothesized that there is no difference in speed of assessment between vascular neurologist (VN) robotic telepresence and standard VN-supervised stroke alert patients in a metropolitan primary stroke center.

Stable feature selection for clinical prediction: exploiting ICD tree structure using Tree-Lasso.

Modern healthcare is getting reshaped by growing Electronic Medical Records (EMR). Recently, these records have been shown of great value towards building clinical prediction models. In EMR data, patients' diseases and hospital interventions are captured through a set of diagnoses and procedures codes. These codes are usually represented in a tree form (e.g. ICD-10 tree) and the codes within a tre...

Comparison of a semi-automatic annotation tool and a natural language processing application for the generation of clinical statement entries.

BACKGROUND AND OBJECTIVE: Electronic medical records with encoded entries should enhance the semantic interoperability of document exchange. However, ...

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapi...

Prioritising lexical patterns to increase axiomatisation in biomedical ontologies. The role of localisation and modularity.

INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Sys...

An eligibility criteria query language for heterogeneous data warehouses.

INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Sys...

Toward a view-oriented approach for aligning RDF-based biomedical repositories.

INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Sys...

Evaluating performance bias in face-to-BMI vision transformer models across diverse human populations

Computer vision models that estimate body mass index (BMI) from facial features offer a non-invasive, low-cost alternative to physical measurement, wi...

Evaluating Clinical Foundation Models for Early Alzheimer's Disease and Related Dementia Prediction from Longitudinal EHRs

Early identification of Alzheimer's disease and related dementias (ADRD) remains challenging despite its importance for timely intervention, managemen...

Import What You Need: Learning When and How to Augment EHR Graphs with External Knowledge

Longitudinal prediction from electronic health records (EHRs) is limited by the sparsity and irregularity in patient trajectories, and knowledge augme...

Unmasking Face Embeddings: Reading, Rendering and Naming with Foundation Models

Modern face recognition (FR) owes much of its success to deep neural networks that learn to extract compact identity embeddings from face images. Thes...

A Multi-Agent Large Language Model Reasoning Engine for Early Detection of Pediatric Growth Disorders

Routine childhood growth surveillance is a cornerstone of pediatric care. Growth pattern abnormalities are often early manifestations of chronic disea...

Machine Learning-Based Prediction of Maternal Morbidity across Heterogeneous Populations in the United States using Sequential Modeling of the All of Us Dataset

In this work, we demonstrate the unprecedented value of NIH's "All of Us Research Program" (AoURP) dataset in studying maternal morbidity and building...

A Pragmatic Randomized Trial of an EHR-Integrated Generative AI Chart Summarization Tool for Ambulatory Clinicians

BACKGROUND Generative AI (genAI) chart summarization tools embedded in electronic health records (EHRs) are being rapidly deployed across U.S. health ...

INTERVenE: Temporal-Abstraction-Interval Based Transformers for Short-Horizon Medical Event Prediction

Electronic Health Record (EHR) prediction models in the intensive care unit must learn from sparse and irregular measurements while preserving the cli...

FedEHR-Agents: Federated Agentic Optimization for Automated EHR Modeling

Recent advances in large language models are enabling autonomous clinical agents to perform increasingly complex electronic health record (EHR) modeli...

NeuroFLAME: A Scalable, Privacy-Preserving Federated Framework for Secure, Reproducible, and Multi-Site Neuroimaging Analysis

Federated analysis offers a scalable approach to multi-site neuroimaging research by enabling distributed statistical modeling, machine learning, deco...

eBPF-Based Cybersecurity Mechanisms: A Systematic Literature Review

Extended Berkeley Packet Filter (eBPF) has emerged as a kernel-level framework enabling dynamic security enforcement in modern operating systems. Whil...

Tensor-Accelerated Eager Multi-Resolution Grids for Evolving Large-Scale Substrates

In neuroevolution, indirect encoding generates neural network connectivity from a compact genome rather than specifying each connection. ES-HyperNEAT ...

Hierarchical MoE for Multi-Modal ILD Diagnosis

Mixture-of-experts (MoE) models combine specialized predictors under learned routing, offering a principled mechanism for leveraging heterogeneity in ...