The integration of artificial intelligence with customer relationship management platforms in healthcare represents a transformative advancement in personalized medicine. This convergence enables healthcare providers to consolidate patient data from diverse sources into unified platforms, facilitating individualized diagnosis and treatment planning. Cloud-based technologies serve as essential infrastructure, providing the scalability and computational capacity necessary for managing complex healthcare data ecosystems. The implementation of standardized APIs and event-driven architectures supports real-time data synchronization across clinical systems, while machine learning algorithms identify subtle patterns within patient data that might otherwise remain undetected. Workflow automation enhances administrative efficiency, reducing documentation burden and enabling clinical staff to focus on direct patient care. The resulting framework supports a multidimensional approach to treatment personalization that incorporates not only clinical data but also patient preferences and social determinants of health, ultimately transforming healthcare delivery toward more responsive, patient-centered models.
R. Dhanasekaran (Mon,) studied this question.