AIMC Topic: Medical History Taking

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Differential Diagnosis Assessment in Ambulatory Care With a Digital Health History Device: Pseudorandomized Study.

JMIR formative research
BACKGROUND: Digital health history devices represent a promising wave of digital tools with the potential to enhance the quality and efficiency of medical consultations. They achieve this by providing physicians with standardized, high-quality patien...

Development and Validation of a Large Language Model-Based System for Medical History-Taking Training: Prospective Multicase Study on Evaluation Stability, Human-AI Consistency, and Transparency.

JMIR medical education
BACKGROUND: History-taking is crucial in medical training. However, current methods often lack consistent feedback and standardized evaluation and have limited access to standardized patient (SP) resources. Artificial intelligence (AI)-powered simula...

Feasibility study of using GPT for history-taking training in medical education: a randomized clinical trial.

BMC medical education
BACKGROUNDS: Traditional methods of teaching history-taking in medical education are limited by scalability and resource intensity. This study aims to assess the effectiveness of simulated patient interactions based on a custom-designed Generative Pr...

Towards conversational diagnostic artificial intelligence.

Nature
At the heart of medicine lies physician-patient dialogue, where skillful history-taking enables effective diagnosis, management and enduring trust. Artificial intelligence (AI) systems capable of diagnostic dialogue could increase accessibility and q...

The feasibility of using generative artificial intelligence for history taking in virtual patients.

BMC research notes
OBJECTIVE: This study aimed to design and develop a virtual patient program using generative Artificial Intelligence (AI) technology, providing medical students opportunities to practice history-taking with a chatbot. We evaluated the feasibility of ...

Mapping and Summarizing the Research on AI Systems for Automating Medical History Taking and Triage: Scoping Review.

Journal of medical Internet research
BACKGROUND: The integration of artificial intelligence (AI) systems for automating medical history taking and triage can significantly enhance patient flow in health care systems. Despite the promising performance of numerous AI studies, only a limit...

Artificial Intelligence (AI)-Based simulators versus simulated patients in undergraduate programs: A protocol for a randomized controlled trial.

BMC medical education
BACKGROUND: Healthcare simulation is critical for medical education, with traditional methods using simulated patients (SPs). Recent advances in artificial intelligence (AI) offer new possibilities with AI-based simulators, introducing limitless oppo...

Diagnostic performances of Claude 3 Opus and Claude 3.5 Sonnet from patient history and key images in Radiology's "Diagnosis Please" cases.

Japanese journal of radiology
PURPOSE: The diagnostic performance of large language artificial intelligence (AI) models when utilizing radiological images has yet to be investigated. We employed Claude 3 Opus (released on March 4, 2024) and Claude 3.5 Sonnet (released on June 21,...

Artificial Intelligence-Powered Hand Surgery Consultation: GPT-4 as an Assistant in a Hand Surgery Outpatient Clinic.

The Journal of hand surgery
PURPOSE: Exploring the integration of artificial intelligence in clinical settings, this study examined the feasibility of using Generative Pretrained Transformer 4 (GPT-4), a large language model, as a consultation assistant in a hand surgery outpat...

Healthcare leaders' experiences of implementing artificial intelligence for medical history-taking and triage in Swedish primary care: an interview study.

BMC primary care
BACKGROUND: Artificial intelligence (AI) holds significant promise for enhancing the efficiency and safety of medical history-taking and triage within primary care. However, there remains a dearth of knowledge concerning the practical implementation ...