Artificial intelligence in internal medicine: knowledge, clinical use and training needs.

Area of Science:

• Medical Informatics
• Artificial Intelligence in Medicine
• Healthcare Technology Adoption

Background:

• Artificial intelligence (AI) is rapidly transforming medical practice.
• Understanding internists' perspectives on AI is crucial for effective integration.

Purpose of the Study:

• To assess self-perceived knowledge, experience, usage, and training needs of AI among Spanish internists.
• To inform the development of targeted educational activities for AI in internal medicine.

Main Methods:

• A cross-sectional study utilizing an anonymous online survey.
• Included demographic, categorical, multiple-choice, and qualitative questions.
• Sample size aimed for 368, with 504 valid responses analyzed.

Main Results:

• Most internists possess basic or intermediate AI knowledge, with higher levels in younger age groups.
• AI is frequently used in clinical practice, research, and teaching.
• Key barriers include lack of training, reliability concerns, ethical issues, and technological limitations.

Conclusions:

• Spanish internists show varied AI knowledge, with younger physicians more proficient.
• Despite barriers like insufficient training, there's a strong demand for AI education and high willingness to adopt AI tools.
• Developing targeted training programs is essential for integrating AI into internal medicine.