AIMC Topic: Trust

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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
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
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
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
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...

Trusting AI made decisions in healthcare by making them explainable.

Science progress
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
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
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...

Increasing Trust in AI Using Explainable Artificial Intelligence for Histopathology - An Overview.

Studies in health technology and informatics
Digital Pathology is an area that could benefit a lot from the automatic classification of scanned microscopic slides. One of the main problems with this is that the experts need to understand and trust the decisions of the system. This paper is an o...

The Representation of Trust in Artificial Intelligence Healthcare Research.

Studies in health technology and informatics
Artificial intelligence (AI) tends to emerge as a relevant component of medical care, previously reserved for medical experts. A key factor for the utilization of AI is the user's trust in the AI itself, respectively the AIt's decision process, but A...