AIMC Topic: Qualitative Research

Clear Filters Showing 251 to 260 of 310 articles

Seven Opportunities for Artificial Intelligence in Primary Care Electronic Visits: Qualitative Study of Staff and Patient Views.

Annals of family medicine
PURPOSE: Increased workload associated with electronic visits (eVisits) in primary care could potentially be decreased by the use of artificial intelligence (AI); however, it is unknown whether this use of AI would be acceptable to staff and patients...

Novel Blended Learning on Artificial Intelligence for Medical Students: Qualitative Interview Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) systems are becoming increasingly relevant in everyday clinical practice, with Food and Drug Administration-approved AI solutions now available in many specialties. This development has far-reaching implicatio...

Practical, epistemic and normative implications of algorithmic bias in healthcare artificial intelligence: a qualitative study of multidisciplinary expert perspectives.

Journal of medical ethics
BACKGROUND: There is a growing concern about artificial intelligence (AI) applications in healthcare that can disadvantage already under-represented and marginalised groups (eg, based on gender or race).

Users' Perceptions and Trust in AI in Direct-to-Consumer mHealth: Qualitative Interview Study.

JMIR mHealth and uHealth
BACKGROUND: The increasing use of direct-to-consumer artificial intelligence (AI)-enabled mobile health (AI-mHealth) apps presents an opportunity for more effective health management and monitoring and expanded mobile health (mHealth) capabilities. H...

What makes a 'good' decision with artificial intelligence? A grounded theory study in paediatric care.

BMJ evidence-based medicine
OBJECTIVE: To develop a framework for good clinical decision-making using machine learning (ML) models for interventional, patient-level decisions.

Patient research priorities in melanoma: a national qualitative interview study.

The British journal of dermatology
BACKGROUND: Outcomes for advanced melanoma have improved following the advent of immunotherapy and targeted therapy. This heralds a need for reconsideration of future research agendas. Patients can - and are keen to - help identify and prioritize res...

Clinical Trust in Data-Driven Decision Support Tools: Qualitative Interview Study.

Studies in health technology and informatics
Data-driven clinical decision support (CDSS) is increasingly available to healthcare practitioners (HCPs), yet little is known about their trust in such tools. Primary care and oncology practitioners were interviewed about their use of data-driven CD...

Participatory Co-Creation of an AI-Supported Patient Information System: A Multi-Method Qualitative Study.

Studies in health technology and informatics
In radiology and other medical fields, informed consent often rely on paper-based forms, which can overwhelm patients with complex terminology. These forms are also resource-intensive. The KIPA project addresses these challenges by developing an AI-a...

Co-Designing a "win-win" in Predictive AI: First Results from Interviews and Focus Groups with Persons with Parkinson's Disease.

Studies in health technology and informatics
This study explored the perspectives of people with Parkinson's disease (PwP) involved in the co-design of AI tools for PD care. The aim was to understand PwP perspectives on AI tools and identify factors influencing their engagement. A qualitative t...

Patients' Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is increasingly used in medical care, particularly in the areas of image recognition and processing. While its practical use in other areas is still limited, an understanding of patients' needs is essential fo...