AIMC Topic: Diagnostic Errors

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CLINICAL REASONING AND ARTIFICIAL INTELLIGENCE: CAN AI REALLY THINK?

Transactions of the American Clinical and Climatological Association
Artificial intelligence (AI) in the form of ChatGPT has rapidly attracted attention from physicians and medical educators. While it holds great promise for more routine medical tasks, may broaden one's differential diagnosis, and may be able to assis...

FROM TEXT TO DIAGNOSE: CHATGPT'S EFFICACY IN MEDICAL DECISION-MAKING.

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: The aim: Evaluate the diagnostic capabilities of the ChatGPT in the field of medical diagnosis.

The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World.

American journal of clinical dermatology
Artificial intelligence (AI) algorithms have been shown to diagnose skin lesions with impressive accuracy in experimental settings. The majority of the literature to date has compared AI and dermatologists as opponents in skin cancer diagnosis. Howev...

Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations.

Medicine
Deep learning algorithms have shown excellent performances in the field of medical image recognition, and practical applications have been made in several medical domains. Little is known about the feasibility and impact of an undetectable adversaria...

The emergence of new trends in clinical laboratory diagnosis.

Saudi medical journal
Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of diseases. Computational approaches are being increasingly used for more precise diagnosis of the clinical p...