Integrating artificial intelligence in healthcare practice: challenges and future prospects

Area of Science:

• Medical Informatics
• Artificial Intelligence in Medicine
• Healthcare Education

Background:

• Artificial intelligence (AI) is increasingly integrated into healthcare settings.
• AI applications offer potential benefits for clinical practice and medical education.
• Existing research highlights the need to assess AI's impact and associated risks.

Purpose of the Study:

• To outline the features of artificial intelligence (AI) applications in healthcare.
• To emphasize specific AI solutions and their integration into medical practice.
• To evaluate the ethical and regulatory risks associated with AI in healthcare.

Main Methods:

• Bibliosemantic analysis of scientific literature and regulatory documents.
• System analysis to compare and generalize AI implementation experiences in healthcare.
• Empirical methods including interviews and modeling for AI-assisted medical care schemes.

Main Results:

• Generative AI is rapidly advancing and currently utilized in healthcare.
• AI tools can aid practicing physicians, patients, and students in clinical case examination and learning.
• Integration of AI into medical training enhances understanding and access to visualization databases.

Conclusions:

• AI technologies are essential for training healthcare professionals in higher medical institutions.
• Key challenges include ethical, regulatory, and system integration issues.
• Further research is needed to develop clear recommendations for AI implementation in medical and educational settings.