Identifying and Reporting Dependent Adult abuse

Embodied Intelligence Applications in Health Care Populations: Scoping Review.

BACKGROUND: Embodied intelligence-artificial intelligence instantiated in physical or virtual bodies that can perceive, communicate, and interact with users and their environments-has been increasingly applied in health care. However, the evidence base remains fragmented because of inconsistent terminology, diverse embodiment forms, and limited synthesis of application domains, target populations,...

Telehealth Scale and Artificial Intelligence Adoption Tiers Across Clinical and Operational Domains in US Hospitals: Cross-Sectional Study.

BACKGROUND: Telehealth expansion and artificial intelligence (AI) adoption are often described as parallel dimensions of health system digital transformation. However, whether telehealth scale is associated with hospital AI adoption and whether this relationship varies across hospital settings remain unclear. OBJECTIVE: This study examined the association of telehealth scale with clinical and oper...

The current state of demographic subgroup reporting for commercially available AI for radiology: a scoping review.

OBJECTIVE: Though subgroup performance reporting helps ensure the safety of artificial intelligence (AI) products, the extent of this reporting remain...

From data to prevention: A systematic review of artificial intelligence applications in sports injury prediction.

PurposeArtificial intelligence (AI) shows considerable potential for sports injury prediction, yet a comprehensive methodological review of its empiri...

Artificial intelligence in dermatology: Clinical promise and environmental impact.

Artificial intelligence (AI) is reshaping dermatology through diagnostic image analysis, clinical documentation, and patient communication tools. Howe...

Comparative evaluation of generative AI models for chest radiograph report generation in the emergency department.

OBJECTIVES: To benchmark medical image-specific vision-language models (VLMs) against real-world radiologist-written reports, focusing on diagnostic q...

Machine Learning for Intraoperative Bleeding Prediction in Patients Undergoing Surgery: Scoping Review.

BACKGROUND: Intraoperative bleeding is a critical event that impacts surgical safety and patient outcomes. Machine learning (ML) has demonstrated pote...

Informatics-Based Psychotherapeutic and Psychiatric Interventions in Dermatology: Scoping Review of Impacts on Skin Disease Severity and Mental Health Outcomes.

BACKGROUND: Chronic dermatologic conditions such as psoriasis, atopic dermatitis, and hidradenitis suppurativa are associated with a high burden of ps...

Prospective validation of an AI algorithm to identify adult-onset type 1 diabetes misclassification: protocol for a non-interventional multicentre study.

INTRODUCTION: Adult-onset type 1 diabetes (T1D) is often misclassified as type 2 diabetes (T2D), resulting in delayed treatment, missed opportunities ...

Predicting Harm: A Systematic Review of Pediatric Pressure Injury Models and Their Clinical Shortcomings.

SIGNIFICANCE: Pediatric pressure injuries (PIs) are a distinct and preventable clinical challenge, yet risk prediction models tailored to children rem...

A multidimensional strategy for identifying quality markers of Radix ginseng-Schisandra chinensis in the disruption of the inflammation-cancer transformation process of hepatocellular carcinoma based on metabolic regulation and chemical properties.

Comprehensive quality control is essential for ensuring the efficacy and safety of traditional Chinese medicines (TCMs). However, current quality cont...

Reinforcement learning for policymaking in epidemic control: A scoping review.

BACKGROUND: Managing an epidemic demands policies that respond at the pace of the outbreak. Conventional rule‑based interventions struggle to keep up,...

Transferrin Receptor 1 (TFRC) and Ferroptosis-Related Biomarkers in Oncology: Analytical Evaluation and Translational Potential.

One of the important regulators of cellular iron uptake is transferrin receptor 1 (TFRC), which is closely linked to ferroptosis, an iron-dependent fo...

G.AI: an AI-driven platform for phenotype standardization, variant interpretation and structured clinical reporting in rare disease genomic diagnosis.

BACKGROUND: The diagnosis of rare diseases increasingly relies on the interpretation of high-throughput next-generation sequencing (NGS) data. As sequ...

Grading and Reporting of Graft-versus-Host Disease in the Modern Era.

Graft-versus-host disease (GVHD) continues to be a major cause of morbidity after allogeneic stem cell transplantation. This article summarizes curren...

An Open-Source Systematic Reviews Integrated System (OSSYRIS) - Streamlining Processes and Standardising Data Structures.

INTRODUCTION: Carrying out a systematic review (SR) of the literature entails a high workload and encompasses a variety of very different tasks. The e...

Use of artificial intelligence in magnetic resonance imaging across the epileptic patient's journey: A meta-analysis of four clinical applications.

OBJECTIVE: The application of artificial intelligence/machine learning (AI/ML) to magnetic resonance imaging (MRI) promises to enhance and support cli...

Cosmin reporting guideline for studies on measurement properties of patient-reported outcome measures and its explanation and elaboration document: translation into Brazilian Portuguese.

PURPOSE: The COSMIN Reporting Guideline 2.0 and its Explanation & Elaboration document have been published to guide researchers in reporting studies o...

Navigating PI-RADS v2.1 in clinical practice: pitfalls, variability, and the supportive role of AI.

Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 has substantially advanced the standardization of prostate MRI acquisition, interpret...

Deep learning for clinically significant prostate cancer detection on MRI: a systematic review, HSROC meta-analysis, and direct comparison with PI-RADS-based interpretation.

OBJECTIVES: To estimate patient-level diagnostic accuracy of deep learning (DL) for MRI-based detection of clinically significant prostate cancer (csP...