State Required CME

Cognitive Sovereignty: An AI-Aware Governance Framework for Neural Data Threats, Autonomous Cyber Defense, and Identity-Aware Security in Neurotechnology Systems.

Neural data collected using brain-computer interfaces, neural implants, and emotion detection systems is analyzed by AI classifiers and agentic architectures to serve purposes such as authentication, access control, and behavioral inference, however, there exists no comprehensive, binding cybersecurity or data protection regime to regulate such neural data. The regulations that currently exist i.e...

Local Deployment of Open-Weight Language Models in Dermatology: Viewpoint on Privacy, Equity, and Practical Implementation.

Generative AI, particularly large language models (LLMs), is reshaping clinical workflows in dermatology. However, cloud-based commercial models pose persistent challenges to Health Insurance Portability and Accountability Act (HIPAA) compliance, especially in dermatology, where protected health information (PHI) extends beyond text to clinical photographs, dermoscopic images, and total-body photo...

The Continuity Trap in Data Science Health Research.

Secondary use is now the ordinary condition of data science health research rather than an exception to it. Electronic health records collected for cl...

Large language models in spine care and research.

BACKGROUND: Large language models (LLMs) have emerged as powerful transformer-based systems capable of capturing long-range dependencies and complex s...

Plastic Surgery Search Engine Optimization in the Artificial Intelligence Era.

Marketing in aesthetic plastic surgery has shifted from traditional print and television toward digital-first strategies, with social media and search...

Building a Natural Language Processing Augmented Information Support System to Enhance Supportive Care for Patients With Prostate Cancer and Families: User-Centered, Iterative Approach.

BACKGROUND: Patients with prostate cancer and their families face significant challenges during transitions from diagnosis to treatment and posttreatm...

Adding Artificial Intelligence to the PERT Improves Time to Diagnosis and Treatment of Pulmonary Embolism.

OBJECTIVES: There is limited data demonstrating the benefit of artificial intelligence technology in the diagnosis and triage of pulmonary embolism. O...

Perspectives of Individuals With Obsessive-Compulsive Disorder on the Role of Artificial Intelligence in Therapy and Treatment: Thematic Qualitative Study.

BACKGROUND: AI has become increasingly used in mental health care for applications such as diagnosis, monitoring, and treatment support. These include...

Addressing the Challenges in Using Synthetic Data for Health Research: Application to Cardiology.

Synthetic data offer significant potential for cardiology research by enabling data sharing, preserving privacy, and supporting machine learning model...

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...

Large Language Models in German Continuing Medical Education Assessments: Protocol for a Fully Crossed Experimental Study.

BACKGROUND: Continuing medical education (CME) is a legal and ethical obligation for physicians in Germany. The rapid rise of large language models (L...

AI-Driven Digital Twin Architecture for Multimodal Prediction and Adaptive Intervention in Cognitive Aging.

Age-related cognitive dysfunction, including mild cognitive impairment and dementia, underscores the need for scalable and personalized predictive mod...

AI-Assisted Clinical Data Abstraction From Electronic Health Records: Retrospective Concordance Study.

BACKGROUND: Manual chart abstraction from electronic health records is a critical step in clinical outcomes research but is time-intensive and prone t...

OphthoChat: A HIPAA-Compliant, Artificial Intelligence-Driven Natural-Language Chatbot for Ophthalmic Electronic Medical Record Querying and Analysis.

PURPOSE: To introduce and evaluate OphthoChat, a Health Insurance Portability and Accountability Act-compliant, artificial intelligence (AI)‑powered n...

Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance.

The convergence of artificial intelligence (AI), blockchain technology, and health care represents one of the most transformative yet technically chal...

CME-KGDTI: integrating clustered mutations into knowledge graph embedding for drug-target interaction prediction.

BACKGROUND: Computational prediction of drug-target interaction (DTI) is critical for drug discovery and precision medicine. Herein, we constructed a ...

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 ...

Federated autoencoder-based clinical decision framework with hybrid class balancing.

Despite diagnosis accuracy has been much improved by depending more on deep learning for disease classification, it raises serious concerns about pati...

AI-Driven Heart Failure Decision Support in Skilled Nursing Facilities.

Heart failure management in skilled nursing facilities (SNFs) is complicated by limited access to specialists, incomplete clinical documentation, and ...