Improving Ophthalmic Care with Artificial Intelligence


Michael Mbagwu, MD, Senior Medical Director

Artificial intelligence (AI) is poised to have a significant impact on ophthalmology in the future, augmenting various aspects of diagnosis, treatment, and patient care. Here are some potential ways AI can help improve ophthalmology in the years to come: 

  1. Automated Screening and Diagnosis: AI algorithms have the ability to analyze ophthalmic images, such as color fundus photos and optic coherence tomography (OCT) images for diagnostic tests, with remarkable accuracy. This can help lead to early detection of eye conditions, such as diabetic retinopathy. AI’s application in other diseases, including glaucoma and macular degeneration, are similarly undergoing research and development. AI can help expedite the screening process, allowing ophthalmologists to focus on improving patient care and increasing access to care.
  2. Enhanced Imaging and Diagnostics: AI can help improve imaging technologies used in ophthalmology, such as OCT. By leveraging AI algorithms, these imaging techniques can help provide more precise and automated measurements, leading to better detection, characterization, and monitoring of eye diseases. 
  3. Treatment Guidance: In the future, AI may assist ophthalmologists in creating personalized treatment plans for patients. By analyzing patient data, AI algorithms can aid in treatment decisions and predict individual treatment outcomes. This can help improve the accuracy and efficacy of treatments such as laser therapies and intravitreal injections.
  4. Surgical Assistance: AI technologies can potentially aid surgeons by providing real-time guidance during ophthalmic procedures. For instance, AI can analyze real time ophthalmic imaging and offer feedback on underlying pathology, incision depth, and tissue manipulation. Such assistance may help enhance surgical precision, reduce complications, and potentially improve patient outcomes. 
  5. Predictive Analytics and Disease Management: AI algorithms can analyze large datasets containing patient records, genetic information, lifestyle factors, and treatment outcomes to identify patterns and develop predictive models, such as geographic atrophy with images. These models can help ophthalmologists predict disease progression, recommend personalized treatments, and optimize long-term management strategies for patients. 
  6. Teleophthalmology and Remote Monitoring: AI-powered teleophthalmology platforms can enable remote screening, diagnosis, and monitoring of eye conditions. Patients can capture OCT images of their eyes using specialized equipment, and AI algorithms can analyze the data and provide preliminary assessments or flag cases that require immediate attention. This approach can help improve access to eye care, especially in underserved areas

AI techniques (e.g., machine learning and natural language processing), combined with clinical expertise, have the potential to positively transform ophthalmic care today and well into the future.

Learn about Verana Health’s advancements in AI that are helping to produce high-quality data in ophthalmology:

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