Information Technology

Digital health technologies in oncology services: a scoping review of clinical implementation, organisational evidence gaps, and policy implications.

INTRODUCTION: Digital health technologies are increasingly used across oncology services, but the available evidence remains concentrated on patient-facing and clinical applications. Organisational perspectives and the involvement of non-clinical professionals remain poorly represented. This scoping review mapped digital health technologies used in adult oncology care, examined their functions for...

Toward diagnostic precision and context-adaptive therapy in prehospital supraventricular tachycardia.

The recent scoping review by Gamberini et al. provides a comprehensive overview of the prehospital diagnosis and management of supraventricular tachycardia (SVT), while highlighting substantial heterogeneity in diagnostic accuracy, therapeutic strategies, and emergency medical service (EMS) practices. In this Matter Arising, we build upon their work by discussing key challenges and opportunities f...

Imminent opioid overdose risk prediction using classical and machine learning survival models following first recorded opioid-related diagnosis: a prospective cohort study from the All of Us research program.

Background: Identifying patients at risk of opioid overdose in healthcare settings is critical, yet evidence on predictive models and their performanc...

Regulatory Approaches to Cybersecurity Risk Management for AI-Enabled Medical Device Software in Korea, the United States, and the European Union: Comparative Document Analysis.

BACKGROUND: Software-based and AI-enabled medical devices are increasingly networked and updatable, expanding the attack surface and making cybersecur...

Balancing technical and social controls across performance measurement and management stages: a bibliometric synthesis of digitally enabled healthcare performance management.

PURPOSE: An integrated, field-level synthesis of digitally enabled performance measurement and management systems (PM/PMS) in healthcare is provided, ...

From fragmented records to living evidence: health system-governed, artificial intelligence-driven, continuously updated real-world clinical data from Truveta.

OBJECTIVES: Real-world data (RWD) have historically suffered from fragmentation, delayed availability, variable data quality, and limited analytic uti...

Reach: Recognising episodes of acute complexity in health: a predictive older patient prioritisation machine learning model.

As the numbers of older people (65 +) rise globally, the pressure on acute hospitals to provide efficient and effective care while addressing resource...

Examining the Roles of Technology Across the Health Care Journey for Individuals With Obsessive-Compulsive Disorder: Qualitative Interview Study.

BACKGROUND: As digital technologies become increasingly embedded in daily life, their roles in mental health care have expanded and diversified. Digit...

End-to-End Clinical Validation of a Human-Supervised Large Language Model Agent for Enterprise Surgical Pathology Reporting.

Large language models (LLMs) show promise for text-based pathology tasks, yet most reported applications remain experimental, lack formal clinical val...

Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records.

BACKGROUND: Screening for atrial fibrillation (AF) on the basis of AF risk may be more effective. We aimed to develop, externally validate, and prospe...

[Concepts and clinical application of digital 3D microscopy].

BACKGROUND: Heads-up 3D surgery is becoming increasingly more important in ophthalmic microsurgery. Digital 3D visualization systems supplement tradit...

[Advances in multi-source medical data-driven identification and spatiotemporal cluster analysis of acute respiratory infections].

Acute respiratory infections (ARIs) are characterized by high morbidity, strong transmissibility, and non-specific clinical manifestations, posing sub...

Mapping Machine Learning-Driven Cybersecurity Solutions in Health Care: Scoping Literature Review.

BACKGROUND: Health care systems face escalating cyberattacks, including the UK Synnovis ransomware attack, which halted pathology services for 14 week...

Multimodal AI in Tissue Diagnostics: Vision-Language Models and the Future of Computational Pathology.

Vision-language models (VLMs) represent an emerging class of multimodal artificial intelligence (AI) systems that integrate visual information with na...

Laboratory medicine 2050: from testing to health intelligence network, a vision from the IFCC Emerging Technologies Division.

Laboratory medicine is undergoing a profound transformation driven by advances in artificial intelligence (AI), automation, and data interoperability....

Artificial intelligence for early detection of diabetic retinopathy: A vision transformer-based approach.

BACKGROUND: Early identification of diabetic retinopathy (DR), which is a primary cause of vision impairment globally, is a crucial phasis for effecti...

Smart wearable biosensors: a transformative synergy between diagnosis and treatment of disease.

Smart wearable biosensors represent a significant paradigm shift from one-time sample analysis to real-time biochemical monitoring at the body interfa...

Characterization and Validation of EHR Computable Phenotypes for Long COVID Using Patient-Reported Symptoms: Insights from the Nationwide RECOVER Program.

OBJECTIVE: Long COVID (LC) remains poorly understood, and there is a critical need for advanced computational tools to better identify and characteriz...

An Interpretable Machine Learning Model for Continuous Prediction of Acute Kidney Injury in Critically Ill Patients With Atrial Fibrillation.

The occurrence of acute kidney injury (AKI) in hospitalized patients with atrial fibrillation (AF) significantly increases the mortality risk. Current...

Understanding end-user contexts and identifying design preferences of an artificial intelligence-based clinical decision support tool for early autism detection.

OBJECTIVES: Building on innovations for autism detection-where artificial intelligence (AI)-based models monitor clinical data within electronic healt...