The potential, limitations, and future of diagnostics enhanced by generative artificial intelligence

Area of Science:

• Medical Diagnostics
• Artificial Intelligence in Medicine
• Clinical Decision Support

Background:

• Generative artificial intelligence (GAI) is rapidly advancing, with significant implications for healthcare.
• The integration of GAI into medical diagnostics is an emerging area of research and development.
• Understanding the capabilities and limitations of GAI is essential for its responsible adoption.

Purpose of the Study:

• To explore the potential applications of GAI in enhancing medical diagnostic processes.
• To identify the limitations and risks associated with using GAI in diagnostics, such as medical misinformation.
• To discuss future directions for GAI development in clinical settings, focusing on augmenting human expertise.

Main Methods:

• Review of current GAI applications and advancements in medical diagnostics.
• Analysis of GAI's role in medical interviews, differential diagnosis, and clinical reasoning.
• Examination through the lens of dual-process theory, supported by recent examples and theoretical frameworks.

Main Results:

• GAI shows promise in translating patient descriptions, providing differential diagnoses, and aiding clinical reasoning.
• Potential for GAI to improve diagnostic speed and accuracy by integrating with intuitive and analytical decision-making.
• Identified limitations include the risk of generating medical misinformation (hallucinations).

Conclusions:

• GAI holds transformative potential for medical diagnostics but requires careful risk management.
• Future GAI advancements should prioritize alignment with human diagnostic reasoning.
• The goal is for GAI to enhance, not replace, the expertise of medical professionals.