Artificial intelligence education in medical imaging: A scoping review

Area of Science:

• Medical Imaging
• Artificial Intelligence Education

Background:

• Healthcare is rapidly integrating Artificial Intelligence (AI), necessitating specialized training for clinical imaging personnel.
• A significant gap exists in formal AI education within medical curricula and synthesized resources for AI training tailored to imaging professionals.

Purpose of the Study:

• To address the question: "What are the current AI training programs or curricula for clinical imaging personnel?"
• To provide an overview of existing AI educational programs in medical imaging.

Main Methods:

• A scoping review following Arksey & O'Malley's framework and PRISMA guidelines.
• Searched six electronic databases from June to September 2023, involving a two-stage screening process.
• Data extraction using a standardized form, summarized thematically and in tables.

Main Results:

• Twenty-two studies were included, focusing on enhancing AI knowledge and practical skills for imaging personnel.
• Curricula covered AI fundamentals to imaging informatics, primarily delivered online, with varied durations and didactic presentations.
• Radiology residents were the main target audience; multidisciplinary teams developed the content. Participant feedback was positive, though time constraints were noted.

Conclusions:

• Existing AI curricula aim to build foundational knowledge, technical skills, and practical application for AI in imaging.
• Future AI education should prioritize evidence-based design, expand to radiographers, enhance imaging informatics content, and utilize diverse teaching strategies and resources.