AIMC Topic: Trust
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[Patient-centered medicine in the era of artificial intelligence: what are the possible implications and risks?].
Recenti progressi in medicina
Mar 1, 2025
Patient-Centered Care (PCC) is currently recognized as the gold standard for the doctor-patient relationship, and numerous studies associate it with the improvement of various outcomes. However, the advent of artificial intelligence (AI) technologies...
The impact of AI feedback on the accuracy of diagnosis, decision switching and trust in radiography.
PloS one
Jan 1, 2025
Artificial intelligence decision support systems have been proposed to assist a struggling National Health Service (NHS) workforce in the United Kingdom. Its implementation in UK healthcare systems has been identified as a priority for deployment. Fe...
Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2025
OBJECTIVES: This study aims to improve the ethical use of machine learning (ML)-based clinical prediction models (CPMs) in shared decision-making for patients with kidney failure on dialysis. We explore factors that inform acceptability, interpretabi...
Care to Explain? AI Explanation Types Differentially Impact Chest Radiograph Diagnostic Performance and Physician Trust in AI.
Radiology
Nov 1, 2024
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...
Initial Investigations into Physician Acceptance of Medical AI: Examining Trust, Resistance, Perceived Job Insecurity, and Usage Intentions.
Studies in health technology and informatics
Aug 22, 2024
This study evaluated physicians' attitudes towards medical AI across three Taiwanese hospitals, focusing on constructs of trust, resistance, job insecurity, and adoption willingness, with a survey based on the Dual-factor Model yielding 282 responses...
Mapping Trust in Nurses with Dimensions of Trustworthy Artificial Intelligence: A Scoping Review.
Studies in health technology and informatics
Jul 24, 2024
This scoping review examines the concept of trust in nursing and its potential application in developing trustworthy Artificial Intelligence (AI) for healthcare. Recognizing nurses as highly trusted professionals, the study explores how attributes co...
Why scientists trust AI too much - and what to do about it.
Nature
Mar 1, 2024
Trusting AI made decisions in healthcare by making them explainable.
Science progress
Jan 1, 2024
OBJECTIVES: In solving the trust issues surrounding machine learning algorithms whose reasoning cannot be understood, advancements can be made toward the integration of machine learning algorithms into mHealth applications. The aim of this paper is t...
Patients' perspectives on the use of artificial intelligence and robots in healthcare.
Bratislavske lekarske listy
Jan 1, 2024
OBJECTIVE: We aimed to evaluate the opinions of individuals aged 18 and above in our country regarding the use of artificial intelligence (AI) and robots in the field of healthcare.
Artificial intelligence and clinical decision support: clinicians' perspectives on trust, trustworthiness, and liability.
Medical law review
Nov 27, 2023
Artificial intelligence (AI) could revolutionise health care, potentially improving clinician decision making and patient safety, and reducing the impact of workforce shortages. However, policymakers and regulators have concerns over whether AI and c...
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