AIMC Topic: Qualitative Research

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Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence-Based Prognosis for Patients With Advanced Solid Tumors.

JCO clinical cancer informatics
PURPOSE: Use of artificial intelligence (AI) in cancer care is increasing. What remains unclear is how best to design patient-facing systems that communicate AI output. With oncologist input, we designed an interface that presents patient-specific, m...

Academic machine learning researchers' ethical perspectives on algorithm development for health care: a qualitative study.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: We set out to describe academic machine learning (ML) researchers' ethical considerations regarding the development of ML tools intended for use in clinical care.

Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review.

The Lancet. Digital health
Machine learning (ML)-based risk prediction models hold the potential to support the health-care setting in several ways; however, use of such models is scarce. We aimed to review health-care professional (HCP) and patient perceptions of ML risk pred...

'Humans think outside the pixels' - Radiologists' perceptions of using artificial intelligence for breast cancer detection in mammography screening in a clinical setting.

Health informatics journal
OBJECTIVE: This study aimed to explore radiologists' views on using an artificial intelligence (AI) tool named ScreenTrustCAD with Philips equipment) as a diagnostic decision support tool in mammography screening during a clinical trial at Capio Sank...

Artificial intelligence in primary care practice: Qualitative study to understand perspectives on using AI to derive patient social data.

Canadian family physician Medecin de famille canadien
OBJECTIVE: To understand the perspectives of primary care clinicians and health system leaders on the use of artificial intelligence (AI) to derive information about patients' social determinants of health.

Developing an AI Tool to Derive Social Determinants of Health for Primary Care Patients: Qualitative Findings From a Codesign Workshop.

Annals of family medicine
PURPOSE: Information about social determinants of health (SDOH) is essential for primary care clinicians in the delivery of equitable, comprehensive care, as well as for program planning and resource allocation. SDOH are rarely captured consistently ...

Healthcare Leaders' Perceptions of the Usefulness of AI Applications in Clinical Work: A Qualitative Study.

Studies in health technology and informatics
Artificial intelligence (AI) is often presented as a technology that changes healthcare and is useful in clinical work in disease prediction, diagnosis, treatment effectiveness, and precision health. This study aimed to explore healthcare leaders' pe...

How, for whom, and in what contexts will artificial intelligence be adopted in pathology? A realist interview study.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: There is increasing interest in using artificial intelligence (AI) in pathology to improve accuracy and efficiency. Studies of clinicians' perceptions of AI have found only moderate acceptability, suggesting further research is needed rega...

Chances and Risks of Using Robotic Assistance Systems in Early Neurological Rehabilitation: A Qualitative Analysis.

Studies in health technology and informatics
Robotic assistance systems offer new therapeutic perspectives for patient mobilization. This work aims to investigate the chances and risks of robotic assistance systems in early neurological rehabilitation. Nine professionals working in physiotherap...