Smart Sensor-Based Point-Of-Care Diagnostics in Ophthalmology: The Potential for Theranocloud as Combination of Theragnostic and Cloud Computing

Recent advances in high-speed network connections, cloud infrastructure, low-cost processing hardware, hardware miniaturization, and powerful learning algorithms like deep learning have revolutionized the healthcare system. These breakthroughs have led to the creation of point-of-care and wearable devices that can reach patients in their homes, enabled by miniaturization and flexible electronics. Moreover, inexpensive cloud connections facilitate the swift transmission of home test results to physicians, and abundant storage servers ensure an encrypted comprehensive anonymous history of the patient's treatment. AI algorithms offer predictive insights and decision-making support for practitioners, exemplified by the recent FDA approved AI software solution for diagnosing diabetic retinopathy in ophthalmology. This chapter explores various smart point-of-care AI algorithms being investigated for the early detection of ophthalmological diseases. The Theranocloud is a futuristic concept for a comprehensive healthcare solution that integrates Therapy, Diagnostics, and Cloud infrastructure to provide affordable and accessible therapy and diagnostic services for patients.