Current Challenges in AI Medicine
- Data Accessibility and Quality
- Integration with Existing Healthcare Systems
- Regulatory and Ethical Hurdles
- Transparency and Explainability of AI Models
- Interoperability and Standardization
- Cybersecurity and Data Privacy Risks
- Workforce Education and Training
- Limited Real-World Validation of AI Models
Future Directions in AI Medicine
- Advancing Personalized Medicine with AI
- Next-Generation AI Algorithms
- AI-Powered Global Health Initiatives
- Emerging Technologies and AI Synergies
- Scalable AI Solutions for Low-Resource Settings
- Collaborative AI Models in Medicine
- AI in Longitudinal and Population Health Studies
- Ethical AI Frameworks for the Future
- AI’s Role in Aging and Longevity Research
- Anticipating Future Regulatory Needs for AI
