Work

Impact of AI Decision Support on Clinical Experts' Radiographic Interpretation of Adamantinomatous Craniopharyngioma.

Year: 2024

Type: article

Abstract: This research explores the integration of Artificial Intelligence (AI) into clinical decision-making in pediatric brain tumor care, specifically Adamantinomatous Craniopharyngioma (ACP). We present a user-centered design approach to introducing AI tools into clinical workflows to support decision-making in managing Central Nervous System tumors. We conducted a controlled experiment with six clinical experts to explore the hypothesis that AI integrated into clinical contexts can improve the radiographic interpretation of ACP. We found that AI assistance reduced task difficulty and enhanced clinical efficiency; we also discovered variations in user behavior during the annotation process. We identified multiple challenges, including the interpretive complexity of radiographic images and increased disagreements among clinicians when AI was employed. Our study underscores the importance of a nuanced understanding of clinician experiences for successful AI integration into a high-stakes clinical workflow.

Source: PubMed Central

Authors: Eric W Prince, David M Mirsky, Todd C Hankinson, Carsten Görg

Institutions: Colorado School of Public Health, University of Colorado Anschutz, Children's Hospital Colorado

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4410761155

FWCI: 0.094

Cites: 1

Cited by: 1

Related to: 10