Medicolegal

Artificial intelligence in medicine: An ethical and legal review.

The integration of artificial intelligence (AI) and machine learning (ML) into medical practice marks a transformative shift within healthcare delivery, diagnostics, and treatment paradigms. Although AI systems exhibit sophisticated capabilities in image recognition, predictive analytics, and clinical decision support, their implementation introduces fundamental ethical and legal questions requiri...

ICU Open-Access Databases for Artificial Intelligence in Sepsis: Balancing Innovation With Data Quality Challenges.

OBJECTIVES: To evaluate the suitability of three major open-access ICU databases (Medical Information Mart for Intensive Care IV [MIMIC-IV], eICU Collaborative Research Database [eICU-CRD], and Amsterdam University Medical Center Database [AmsterdamUMCdb]) for artificial intelligence (AI)-based sepsis research, with a focus on data completeness, internal consistency, terminological standardization...

Target-biology and interactome-derived signatures predict target-level associations with safety-related drug attrition.

Clinical drug development suffers from high rates of toxicity-related failure despite the use of compound-centric preclinical safety screening, with a...

Community Plastic Reconstructive and Aesthetic Surgery: A Proposal.

BACKGROUND: Plastic, Reconstructive, and Aesthetic Surgery (PRAS) faces domain erosion from adjacent specialties and jurisdictional competition. To ma...

Using artificial intelligence in clinical practice: Royal Australasian College of Physicians position statement.

The Royal Australasian College of Physicians (RACP) has recently issued a position statement titled 'Using artificial intelligence in clinical practic...

Targeting GLS and LPIN2 in renal fibroblasts: potential therapeutic targets for kidney stone disease identified by integrated multi-omics analysis.

Kidney stones (KS) are a common urological condition, the aetiology of which remains incompletely understood. This study aimed to investigate the key ...

Testing Knowledge Boundaries: Adversarial Evaluation of LLMs for Antimicrobial Stewardship.

OBJECTIVES: Evaluate whether general-purpose large language models (LLMs) demonstrate competencies suitable for antimicrobial stewardship (AMS) suppor...

A Human-Governed Clinical Informatics Framework for Safe AI-Assisted Mental Health Counseling: Secondary Framework Development and Requirement Mapping Study.

BACKGROUND: Natural language processing and large language model systems are increasingly used to support mental health documentation, screening, and ...

A physics-informed decomposition network for carbon ion radiotherapy dose monitoring: a proof-of-concept study.

In-beam positron emission tomography (PET) provides a promising strategy for dose monitoring in carbon ion radiotherapy (CIRT), but accurate dose pred...

Large Language Models in Spine Surgery: A Scoping Review of Clinical Efficacy, Technical Integration, and Ethical Paradigms.

Study DesignScoping review.ObjectivesTo map spine literature on large language models, characterize reported use cases, and identify evidence gaps lim...

Perceptions, knowledge and adoption of artificial intelligence in rheumatology: results from a British Society for Rheumatology survey.

OBJECTIVES: Artificial intelligence (AI) and machine learning applications are rapidly expanding across healthcare. Successful implementation of AI te...

Coronary Artery Calcification: Contemporary Diagnosis from Invasive Imaging to Percutaneous Treatment.

Coronary artery calcification (CAC) represents a significant challenge in contemporary interventional cardiology, substantially affecting percutaneous...

Responsible and innovative AI for mental health care: five priority themes.

Artificial intelligence (AI) has entered psychiatry at scale, yet its clinical impact remains constrained by a sizable gap between technical validatio...

AI in academia: navigating ethical crossroads of innovation, integrity, and equity.

The recent integration of artificial intelligence (AI) into academia could usher in transformative efficiencies across scholarly workflows-from manusc...

Turning Pages Into Pixels: Leveraging Technology and Artificial Intelligence in Nursing Professional Development.

Nursing professional development practitioners manage complex systems supporting onboarding, competency validation, continuing education, and regulato...

Nonporous Metal-Organic Framework Enables Record‑High Uranium Extraction and Complete Diglyme Degradation.

Nuclear energy accommodates rising energy demand of artificial intelligence yet poses environmental risks, making uranium extraction from wastewater i...

[Artificial intelligence in the preparation of clinical expert opinions : Current evidence, use cases, and limitations in orthopedic assessment].

BACKGROUND: Generative AI, large language models, and ambient AI systems are rapidly being integrated into documentation-related processes in medicine...

SMART: structured, meaningful, auditable, responsible, and transparent documentation for clinical AI.

OBJECTIVE: Clinical AI systems and models increasingly need traceable documentation that makes intended use, performance evidence, transparency, and l...

The Rise of Natural Language Processing and the Fall of the Illness Narrative in Clinical Documentation.

The integration of artificial intelligence (AI) into clinical documentation is reshaping infectious diseases (ID) outpatient practice. While natural l...

Ethical considerations in generative artificial intelligence for synthetic data generation in ophthalmology.

Generative artificial intelligence (AI) is beginning to reshape medical research, with ophthalmology at the forefront of this transformation. This nar...