AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Physicians

Showing 21 to 30 of 275 articles

Clear Filters

Comparison of the experience and perception of artificial intelligence among practicing doctors and medical students.

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: Aim: To analyze and compare the experiences and perceptions of artificial intelligence (AI) among practicing doctors and medical students.

Ambient artificial intelligence scribes: physician burnout and perspectives on usability and documentation burden.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This study evaluates the pilot implementation of ambient AI scribe technology to assess physician perspectives on usability and the impact on physician burden and burnout.

Physicians' ethical concerns about artificial intelligence in medicine: a qualitative study: .

Frontiers in public health
BACKGROUND/AIM: Artificial Intelligence (AI) is the capability of computational systems to perform tasks that require human-like cognitive functions, such as reasoning, learning, and decision-making. Unlike human intelligence, AI does not involve sen...

[ARTIFICIAL INTELLIGENCE AND MEDICAL ETHICS].

Harefuah
Artificial intelligence has burst into our lives with great vigor in recent years. We encounter it in all areas of life, as well as in the field of medicine. The article refers to medical ethics in two areas: One field is medicine based on Mega Data ...

Explainability of artificial neural network in predicting career fulfilment among medical doctors in developing nations: Applicability and implications.

Social science & medicine (1982)
BACKGROUND: Career fulfilment among medical doctors is crucial for job satisfaction, retention, and healthcare quality, especially in developing nations with challenging healthcare systems. Traditional career guidance methods struggle to address the ...

Should AI models be explainable to clinicians?

Critical care (London, England)
In the high-stakes realm of critical care, where daily decisions are crucial and clear communication is paramount, comprehending the rationale behind Artificial Intelligence (AI)-driven decisions appears essential. While AI has the potential to impro...

Interpretable time-series neural turing machine for prognostic prediction of patients with type 2 diabetes in physician-pharmacist collaborative clinics.

International journal of medical informatics
BACKGROUND: Type 2 diabetes (T2D) has become a serious health threat globally. However, the existing approaches for diabetes prediction mainly had difficulty in addressing multiple time-series features. This study aims to provide an adjunctive tool f...

Facilitating Trust Calibration in Artificial Intelligence-Driven Diagnostic Decision Support Systems for Determining Physicians' Diagnostic Accuracy: Quasi-Experimental Study.

JMIR formative research
BACKGROUND: Diagnostic errors are significant problems in medical care. Despite the usefulness of artificial intelligence (AI)-based diagnostic decision support systems, the overreliance of physicians on AI-generated diagnoses may lead to diagnostic ...

Evaluating the concordance of ChatGPT and physician recommendations for bariatric surgery.

Canadian journal of physiology and pharmacology
Integrating artificial intelligence (AI) into healthcare prompts the need to measure its proficiency relative to human experts. This study evaluates the proficiency of ChatGPT, an OpenAI language model, in offering guidance concerning bariatric surge...

Care to Explain? AI Explanation Types Differentially Impact Chest Radiograph Diagnostic Performance and Physician Trust in AI.

Radiology
Background It is unclear whether artificial intelligence (AI) explanations help or hurt radiologists and other physicians in AI-assisted radiologic diagnostic decision-making. Purpose To test whether the type of AI explanation and the correctness and...