Integrating Artificial Intelligence Into Telemedicine: Evidence, Challenges, and Future Directions

Area of Science:

• Medical Informatics
• Artificial Intelligence
• Digital Health

Background:

• Telemedicine offers remote healthcare but faces challenges like workload and data variability.
• Artificial intelligence (AI) presents opportunities for automation and enhanced analysis in healthcare.
• Integrating AI into telemedicine introduces ethical, regulatory, and implementation hurdles.

Purpose of the Study:

• To review the role of AI in telemedicine.
• To identify key applications, challenges, and future directions of AI in remote healthcare.
• To evaluate the impact of AI on diagnostic accuracy and patient monitoring in telemedicine.

Main Methods:

• Systematic literature search in PubMed and Cochrane Library (2015-2024).
• Adherence to PRISMA guidelines for study selection.
• Thematic evaluation of 31 selected articles for trends, barriers, and innovations.

Main Results:

• AI demonstrates success in dermatology (image analysis) and ophthalmology (diabetic retinopathy screening).
• AI-powered tools improve mental health support, patient triage, and continuous monitoring via wearables.
• Emerging technologies like blockchain and decentralized AI aim to enhance data protection in telemedicine.

Conclusions:

• AI integration significantly enhances telemedicine, improving diagnostic accuracy and remote patient monitoring across specialties.
• Real-world validation, ethical considerations, regulatory compliance, and model generalizability remain key challenges.
• Future research should focus on interoperability, standardized guidelines, and privacy-preserving AI for widespread adoption.