Bridging the gap between scientists and clinicians: addressing collaboration challenges in clinical AI integration

Area of Science:

• Medical Informatics
• Artificial Intelligence in Medicine
• Perioperative Medicine

Background:

• Challenges exist in integrating artificial intelligence (AI) into healthcare settings, particularly between scientific and clinical communities.
• Effective AI implementation requires addressing barriers to interdisciplinary collaboration and understanding.

Discussion:

• Interdisciplinary research centers are vital for fostering collaboration between AI developers and healthcare professionals.
• Diversity, equity, and inclusion are crucial for developing and implementing AI solutions that benefit all patient populations.
• Addressing the gap requires focused efforts on communication, shared understanding, and mutual respect.

Key Insights:

• Successful AI integration hinges on overcoming the disconnect between AI researchers and clinical practitioners.
• Ethical considerations and inclusive practices are paramount for trustworthy AI in medicine.
• Tailored education and training programs can enhance AI adoption and efficacy in clinical workflows.

Outlook:

• Future advancements in AI for perioperative medicine depend on sustained interdisciplinary collaboration and ethical frameworks.
• Continued focus on diversity, equity, and inclusion will ensure equitable AI benefits in healthcare.
• Optimizing AI's impact necessitates a unified approach involving scientists, clinicians, and policymakers.