Information Technology

Pre-Imaging Clinical Factors Associated With Cardiac MR Image Quality Using Large Language Model-Enabled Data Extraction.

BACKGROUND: Poor cardiac MR image quality can prompt repeat examinations and hinder clinical decision-making. PURPOSE: To evaluate whether pre-imaging clinical information, extracted using a large language model (LLM), is independently associated with cardiac MR image quality. STUDY TYPE: Retrospective. POPULATION: 1006 adults undergoing clinical cardiac MR examinations. FIELD STRENGTH/SEQUENCE: 1...

Evaluating open-source LLMs for dental EMR generation.

Automatic selection of optical coherence tomography images for prognostic prediction models in age-related macular degeneration.

BACKGROUND AND OBJECTIVE: Age-related macular degeneration (AMD) is a leading cause of blindness. Current standard treatments require frequent intravi...

Association between diagnostic history and cancer incidence within 5 years: a real-world observational analysis.

Cancer is associated with many pre-existing health conditions (PHCs), but accurately quantifying these links remains challenging. Although some studie...

Comparing regular expression and machine learning approaches to predict immigrant status from primary care electronic medical record data in Ontario, Canada.

New immigrants often face barriers when navigating the healthcare system, which can create unmet healthcare needs and contribute to health inequities....

An explainable multi-head attention network for healthcare IoT threat detection based on the MedDefender-MHAN framework.

The rapid proliferation of Internet of Medical Things (IoMT) devices in healthcare environments has created critical cybersecurity vulnerabilities tha...

Architectural and translational perspectives on clinical decision support systems for rare disease diagnosis: a scoping review.

BACKGROUND: Rare diseases remain difficult to diagnose because of phenotypic heterogeneity, limited clinical familiarity, and fragmented health data i...

Interpretable multimodal PET/CT-EHR fusion via mixture-of-experts for prognostic stratification in mantle cell lymphoma: a multicenter study.

BACKGROUND: Mantle cell lymphoma (MCL) is a rare, biologically heterogeneous B-cell malignancy with highly variable outcomes. Existing prognostic tool...

Targeted use of large language models for EHR-based computable phenotyping.

OBJECTIVE: Computable phenotypes derived from electronic health records (EHRs) are central to clinical research and quality reporting. Although large ...

Development of a Contextualized, Research-Based Flemish Assessment Framework for Digital Care, Assistance, and Support: Delphi Study.

BACKGROUND: The rapid evolution of digital technologies has transformed health, mental health, and social care, offering new modalities of digital car...

Building a tactical medical chatbot for conflict and low-resource settings: A low-code platform approach.

BACKGROUND: Conflict zones severely disrupt healthcare access, with millions affected by armed conflicts. The lack of standardized medical guidance ex...

Estimate renal cell carcinoma recurrence rates using electronic health records.

BACKGROUND: Lack of readily available recurrence data has limited the use of electronic health records (EHR) for risk assessment of cancer recurrence ...

Clinical accuracy and applications of the Pediatric Assessment Triangle in emergency care: a narrative review.

BACKGROUND: The Pediatric Assessment Triangle (PAT) is a rapid visual assessment framework designed to support early identification of critically ill ...

The impact of integrating artificial intelligence into regulatory affairs functions in the Medtech industry.

INTRODUCTION: Artificial intelligence is becoming an important tool in the medical technology industry where its implementation has the potential to s...

Inferring rheumatoid arthritis disease activity status from the electronic health records across health systems.

OBJECTIVE: Disease activity plays a central role in rheumatoid arthritis (RA) clinical studies. The inconsistent availability of data on disease activ...

Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement.

BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitorin...

Performance of Machine Learning Models for Sepsis and Stroke Detection Using EMS Data.

OBJECTIVES: Early sepsis and stroke recognition by emergency medical services (EMS) improves triage, treatment, and patient outcomes. Machine learning...

Digital twin applications in radiology and radiotherapy: Applications, challenges, and future perspectives.

Digital twin technology has emerged as a transformative innovation in healthcare, offering virtual replicas of physical entities at patient-level, equ...

A novel multi-stage attack dataset for smart home intrusion detection.

Modern homes are increasingly relying on networks of internet-connected devices for smart home applications. Unlike an enterprise network, such smart ...

[Expert consensus on optimizing the multidisciplinary clinical pathways and management models for pulmonary function testing].

The promotion and application of pulmonary function tests (PFTs) in China have achieved preliminary success;however, numerous deficiencies persist in ...