AI Medical Compendium Topic

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Clinical Decision-Making

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Monitoring performance of clinical artificial intelligence in health care: a scoping review.

JBI evidence synthesis
OBJECTIVE: The objective of this review was to provide an overview of the diverse methods described, tested, or implemented for monitoring performance of clinical artificial intelligence (AI) systems, while also summarizing the arguments given for or...

Qualitative metrics from the biomedical literature for evaluating large language models in clinical decision-making: a narrative review.

BMC medical informatics and decision making
BACKGROUND: The large language models (LLMs), most notably ChatGPT, released since November 30, 2022, have prompted shifting attention to their use in medicine, particularly for supporting clinical decision-making. However, there is little consensus ...

Artificial Intelligence in Diagnosing and Managing Vascular Surgery Patients: An Experimental Study Using the GPT-4 Model.

Annals of vascular surgery
BACKGROUND: The introduction of artificial intelligence (AI) has led to groundbreaking advancements across many scientific fields. Machine learning algorithms have enabled AI models to learn, adapt, and solve complex problems in previously unimaginab...

Evaluating ChatGPT's competency in radiation oncology: A comprehensive assessment across clinical scenarios.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Artificial intelligence (AI) and machine learning present an opportunity to enhance clinical decision-making in radiation oncology. This study aims to evaluate the competency of ChatGPT, an AI language model, in interpreting clinical scenari...

Smart data-driven medical decisions through collective and individual anomaly detection in healthcare time series.

International journal of medical informatics
BACKGROUND: Anomalies in healthcare refer to deviation from the norm of unusual or unexpected patterns or activities related to patients, diseases or medical centres. Detecting these anomalies is crucial for timely interventions and efficient decisio...

Applications and potential of machine, learning augmented chest X-ray interpretation in cardiology.

Minerva cardiology and angiology
The chest X-ray (CXR) has a wide range of clinical indications in the field of cardiology, from the assessment of acute pathology to disease surveillance and screening. Despite many technological advancements, CXR interpretation error rates have rema...

Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine.

Journal of general internal medicine
Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended conse...

Bias Sensitivity in Diagnostic Decision-Making: Comparing ChatGPT with Residents.

Journal of general internal medicine
BACKGROUND: Diagnostic errors, often due to biases in clinical reasoning, significantly affect patient care. While artificial intelligence chatbots like ChatGPT could help mitigate such biases, their potential susceptibility to biases is unknown.