Information Technology

Football cybersecurity threat severity prediction using multi-head transformer-based deep learning models.

The power, potential of real-world data in randomized controlled trials: proceedings from a multistakeholder think tank.

Randomized controlled trials (RCTs) remain the gold standard for evaluating medical interventions, but they often face challenges related to patient recruitment, cost, and efficiency. Real-world data (RWD) has emerged as a valuable tool to enhance trial design, improve patient identification, and support regulatory decision-making. However, integrating RWD into RCTs presents methodological, regula...

Imputation Free Deep Survival Prediction with Conditional Variational Autoencoders.

UNLABELLED: Electronic Health Records (EHRs) provide rich opportunities for developing risk prediction tools to support clinical decision-making, yet ...

Privacy-preserving multimodal federated learning pipeline for cyber-resilient healthcare systems.

The integration of Internet of Things (IoT) devices and electronic medical records (EMRs) has transformed healthcare delivery but has also created new...

Electronic health record-based prediction models for dementia detection: a systematic review of model performance and quality.

OBJECTIVES: Leveraging routine electronic health records (EHR) for dementia detection is a growing field, but quality and clinical utility of existing...

K-STAMM: a knowledge-enhanced spatial - temporal attention model with multimodal fusion for pneumonia prediction.

Precise prediction of pneumonia remains a challenge mainly because effective integration of clinical data that are highly heterogeneous is mandatory. ...

An interpretable deep learning framework for predictive modeling of postoperative infections in ICU patients.

A significant proportion of intensive care unit (ICU) patients undergo surgical procedures, and some may develop postoperative infections. Accurately ...

A birth certificate for data to improve findability, accountability, and traceability.

Data quality is the foundational to scientific research and the rapid advancement of artificial intelligence. Ensuring data quality, provenance, and r...

Predicting Electronic Health Record Usability: Scoping Review of Adoption Models, Metrics, and Future Directions.

BACKGROUND: Electronic health records (EHRs) play an essential role in modern health care, enabling data sharing and improving patient safety; however...

ClinicRealm: Re-evaluating large language models with conventional machine learning for non-generative clinical prediction tasks.

Large Language Models (LLMs) are increasingly deployed in medicine. However, their utility for non-generative clinical prediction is under-evaluated, ...

irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.

BACKGROUND: Large language models (LLMs) have emerged as transformative technologies, revolutionising natural language understanding and generation ac...

Assessment of Telemedicine Perceptions, Usability, and Implementation Barriers Among Physicians in Kazakhstan Using the Telehealth Usability Questionnaire-Model for Assessment of Telemedicine-Kazakhstan Version (TUQ-MAST-KZ) Questionnaire: Pilot Cross-Sectional Survey Study.

BACKGROUND: Health care professionals' perceptions of telemedicine, its usability, and the presence of organizational barriers are important determina...

Cost-effectiveness analysis of resective epilepsy surgery in drug-resistant patients: an artificial intelligence data modeling.

BACKGROUND: Resective epilepsy surgery has been proven to reduce the number of seizures and improve quality of life in patients with drug-resistant ep...

Technology Matters: Emerging technologies in clinical informatics to support child and adolescent mental healthcare safety.

Electronic health records (EHRs) can support patient safety across medical settings but require thoughtful adaptation to serve specialty care. This ar...

From Chatbot to Care Team: A Pilot Study of Generative Artificial Intelligence to Support Nurse-Pharmacist Collaboration and Patient Care in Telemedicine.

Background: Collaboration between nurse practitioners (NPs) and pharmacists is essential for comprehensive patient care, especially in telehealth sett...

Using natural language processing to assess MDD psychotherapy patterns among Veterans Affairs patients with suicide risk.

Major depressive disorder (MDD) is a leading risk factor for suicide. Within the US Department of Veterans Affairs (VA), psychotherapy is widely used ...

EHR-derived cognitive load is associated with guideline-concordant statin initiation in primary care.

INTRODUCTION: Linking electronic health record (EHR) use to care quality may offer insights into potential interventions improving guideline adherence...

Artificial Intelligence, Connected Care, and Enabling Digital Health Technologies in Rare Diseases With a Focus on Lysosomal Storage Disorders: Scoping Review.

BACKGROUND: Rare diseases affect more than 300 million people globally, and only about 5% have approved therapies. Lysosomal storage disorders (LSDs) ...

Precision Risk Model Using Quantitative Assessment of Vascular Severity in Telemedicine-Based Screening.

IMPORTANCE: Retinopathy of prematurity (ROP) screening requires frequent examinations to avoid missed treatment-requiring disease, but this approach i...

Semantic interoperability and price analytics in hospital transparency data: a multi-stage pipeline with NLP and machine learning.

PURPOSE: The U.S. Hospital Price Transparency mandate requires public disclosure of machine-readable files (MRFs), yet profound data heterogeneity hin...