AI in Ophthalmology. With Prof Pearse Keane- Consultant Ophthalmologist at Moorfields and Professor of Artificial Medical Intelligence at University College London
Nov 11, 2024
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Pearse Keane, a Consultant Ophthalmologist at Moorfields and a Professor of Artificial Medical Intelligence at University College London, dives into the transformative role of AI in eye care. He shares insights on the successful collaboration between Moorfields and Google DeepMind to detect retinal diseases. Discover the emerging field of 'oculomics,' viewing the eye as a vital health indicator. Keane also discusses the UK’s potential to lead in healthcare AI by merging NHS data with academic expertise and the innovative ReptFound model for enhancing eye disease screenings.
The collaboration between Moorfields and Google DeepMind has advanced AI capabilities in detecting retinal diseases, matching expert diagnoses.
The emerging field of oculomics highlights how eye examinations can reveal systemic health issues, enabling early diagnoses for various conditions.
Deep dives
Advancements in AI for Eye Care
AI has made significant strides in ophthalmology, particularly in detecting and diagnosing retinal diseases. One of the notable collaborations was between Moorfields Eye Hospital and Google DeepMind, focusing on the development of AI systems that can analyze retinal scans. These AI models have proven to match, if not surpass, the diagnostic capabilities of experienced clinicians in identifying various retinal conditions. The success of these efforts has positioned ophthalmology at the forefront of medical AI advancements.
Oculomics: The Eye as a Portal to General Health
The concept of oculomics emphasizes the potential of eye examinations to reveal information about systemic health issues. Recent studies have suggested that retinal images can indicate risk factors for conditions such as cardiovascular diseases, Alzheimer's, and Parkinson's. The ability to detect subtle changes in the retina could enable early diagnoses, potentially up to seven years prior to clinical identification of such diseases. This growing understanding opens new avenues for predictive healthcare leveraging eye health data.
Challenges in AI Translation to Clinical Practice
Transitioning AI models from research to practical clinical applications presents numerous challenges. Regulatory compliance, software refactoring, and quality management need careful attention to ensure that AI systems function reliably in clinical settings. Furthermore, establishing a sustainable business model for AI integration into healthcare is critical, as these developments require considerable financial investment and ongoing support. The complexity of these factors underscores the careful planning needed for successful implementation.
Future of AI Foundation Models in Ophthalmology
Looking ahead, the development of foundation models like RETFound indicates a promising direction for AI in ophthalmology. These models can leverage extensive retinal imaging datasets to identify diverse downstream tasks ranging from disease screening to broader health insights. Upcoming initiatives aim to amplify this work by integrating a more extensive global dataset, potentially improving accuracy and applicability across different demographics. The evolution of these models could revolutionize the role of AI in clinical care, making diagnostics more inclusive and efficient.
In this episode Prof Pearse Keane- Consultant Ophthalmologist at Moorfields and Professor of Artificial Medical Intelligence at University College London discusses AI in Ophthalmology.
Conversation topics include:
The story of the Moorfields- Google Deep Mind collaboration and the use of AI to detect retinal diseases
The birth of 'oculomics' as a field: Using the eye as a window to the rest of the body
The practical challenges of moving from code to clinic when it comes to Healthcare AI
The potential for the UK to be a world leader in healthcare AI by linking NHS data with top universities
Medical foundation models and their role in the future of healthcare
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