Information Technology

Evaluating the Performance of Large Language Models for Generating Emergency Department Discharge Instructions.

BACKGROUND: Clear discharge instructions are essential for safe emergency department (ED) care, yet creating patient-centered, health literate materials remain challenging. Large language models (LLMs) may improve patient communication, but their role in the ED remains underexplored. OBJECTIVE: The objective of this study was to evaluate the feasibility of using LLMs to generate ED discharge instr...

[Expert consensus on the clinical application of robotic-assisted bronchoscopy].

Robotic-assisted bronchoscopy (RAB) is an emerging diagnostic and interventional technology which integrates thin-slice CT-based virtual airway reconstruction, precise navigation, and stable robotic manipulation.It has been shown to offer clear advantages in the management of peripheral pulmonary lesions. With the rapid increase in clinical adoption in China, standardized guidance is required to e...

AI-powered Chatbot integration for enhanced accessibility of electronic health records in a pediatric hospital.

Navigating electronic health records (EHRs) remains a time-consuming task for clinicians, especially in resource-constrained healthcare settings. This...

AI-Powered Documentation for Mental Health Providers: Retrospective Observational Mixed Methods Study.

BACKGROUND: Mental health providers (MHPs) face a significant administrative burden from documentation, which can contribute to burnout and reduce tim...

Roadmap: An Ontology of Medical AI Models and Datasets.

Successful development, regulatory review, and clinical implementation of artificial intelligence (AI) systems in medicine require clear, unambiguous ...

Bird-inspired optimization approach using taper-shape transfer function for intrusion detection in IoT networks.

The Internet of Things (IoT) has emerged as a pervasive technological paradigm that interconnects heterogeneous devices and sensors, enabling continuo...

Toward self-driving laboratory 2.0 for chemistry and materials discovery.

The convergence of laboratory automation, artificial intelligence (AI), and data-driven science has catalyzed the emergence of self-driving laboratori...

Investigating the Effect of Hospital Infection Control Informatization on Optimizing Microbiological Specimen Submission Before Antibiotic Therapy: Failure Mode and Effects Analysis.

BACKGROUND: Antimicrobial resistance (AMR) poses a critical global health threat, with inappropriate antibiotic use being a major driver. Timely micro...

Non-contact monitoring in neonatology.

To present and critically evaluate current contactless monitoring modalities - infrared thermography (IRT), photoplethysmography imaging (PPGI), balli...

Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities.

OBJECTIVES: To analyse the landscape of active US National Institutes of Health (NIH) artificial intelligence (AI) health research grants, with emphas...

Bridging immunization gaps in Sub-Saharan Africa: a narrative review of microplanning, geospatial, and machine learning approaches to reach zero-dose children and under-immunised children.

Immunization inequities persist across Sub-Saharan Africa, with significant numbers of zero-dose and under-immunised children contributing to preventa...

Telepathology and Mobile Health System for Province-Wide Pathology Consultation in Henan, China: Retrospective Evaluation Study.

BACKGROUND: Telepathology has emerged as a transformative digital health solution to address the global shortage of pathologists and the unequal distr...

Improving Maternal Health Equity and Outcomes Through the Development of a Clinician-Informed Algorithm: A Feasibility Study.

OBJECTIVE: Increasing proportions of adverse maternal health outcomes occur in the 12-month postpartum period and could be addressed in outpatient set...

MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management.

This perspective introduces MS360°, a conceptual hybrid care model for the management of multiple sclerosis (MS). It integrates traditional on-site as...

Machine learning-based prediction of sudden cardiac death in the general population using electronic health record data.

AIMS: The vast majority of sudden cardiac death (SCD) cases occur in the general population with few known risk factors instead of just patients alrea...

Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study.

BACKGROUND: Chronic back pain is a severe health condition with underlying biopsychosocial factors that make diagnosis difficult, and pain chronicity ...

Applications and Challenges of Artificial Intelligence and Big Data in Drug Regulation.

Artificial intelligence (AI) and big data are increasingly applied in drug regulation and have demonstrated significant potential worldwide. The U.S. ...

Improving classification of myocardial infarction with machine learning in a diverse population.

Phenotype classification with electronic health record (EHR) data is increasingly performed with machine learning (ML); however, their performance in ...

Artificial intelligence for automated detection of joint bleeding via ultrasound in hemophilia: advancing standardization.

BACKGROUND: Musculoskeletal ultrasound (US) is a noninvasive tool for joint assessment in persons with hemophilia. Early detection of joint bleeding u...

CTKGR: temporal knowledge graph enhanced prediction of in-hospital events for pneumonia patients using electronic health records.

OBJECTIVE: This study aims to develop an advanced clinical event prediction model leveraging the temporal characteristics embedded within electronic h...