Latest AI and machine learning research in patient safety / risk management for healthcare professionals.
BACKGROUND: Electronic early warning/track-and-trigger systems (EW/TTS) are crucial for patient monitoring, detecting clinical deterioration (CD), and activating rapid response teams. Understanding the current level of automation in EW/TTS is essential. OBJECTIVE: This study aimed to provide a comprehensive overview and critical assessment of electronic EW/TTS, including automated features, algori...
BACKGROUND: Patient safety investigation reports support organizational learning only when they are complete, usable, and sufficiently detailed. Conventional free-text reports are often inconsistent and may omit information needed for review and learning. Project NARRATE (Nursing AI-Refined for Accurate Transcription of Events) is a nursing-led ambient artificial intelligence workflow that uses pr...
OBJECTIVE: To evaluate the accuracy and reliability of three AI platforms ChatGPT, Perplexity, and Google Gemini in assessing the methodological quali...
OBJECTIVES: Patients increasingly use large language models (LLMs) for health information, yet their use patterns, perceptions, and impact on clinical...
BACKGROUND: Large language models (LLMs) are increasingly used in higher education, but multi-country evidence on dental students' use, verification, ...
OBJECTIVE: This discussion paper conceptualizes cognitive fog as a communication and reasoning problem that can emerge when clinicians, patients, or o...
The line between tool and companion was once obvious, but conversational AI is blurring it in ways few researchers anticipated. Large language model c...
BACKGROUND: Preoperative templating in total hip arthroplasty (THA) optimizes implant sizing and positioning accuracy. Standard practice relies on two...
Artificial intelligence generated advertising is widely adopted in retailing and consumer services, yet its effects on trust, engagement, and purchase...
BACKGROUND: The integration of ambient artificial intelligence (AI) scribes into the OpenNotes environment presents a profound governance crisis in he...
BACKGROUND: Stress, as commonly recognized, is an integral part of modern life and can significantly affect both mental and physical health. While sub...
BACKGROUND: Machine learning models for Obstructive Sleep Apnea (OSA) diagnosis have largely inherited some structural limitations: reliance on generi...
Evidence-based medicine revolutionized clinical practice, bringing expectations that physician-patient communication should be similarly transparent a...
The emergence of large language models and generative artificial intelligence (AI) is driving fundamental transformations in the ecosystem of scholarl...
As artificial intelligence (AI), particularly generative AI, is being actively introduced and utilized in medical research and manuscript writing, new...
The use of generative artificial intelligence (AI) in scholarly publishing is expanding rapidly, yet clear standards for its appropriate use and discl...
The public release of large language models (LLMs) in late 2022 has fundamentally altered the landscape of scholarly medical publishing. LLMs now perm...
The rapid adoption of large language models and generative artificial intelligence (AI) is transforming biomedical research and publishing. Although i...
PURPOSE: Ultra-widefield (UWF) fundus cameras capture a larger retinal area without pupil dilation. We summarized evidence and diagnostic performance ...