The eye is a unique window to overall health. Its associated medical imaging has great characteristics, such as being non-invasive, convenient, and rich in information, which offers significant potential for developing new technologies for diagnosing systemic diseases.
Progress in the diagnosis of systemic diseases based on ophthalmic imaging artificial intelligence technologyInterconnections between the eye and systemic health. This schematic illustrates the correlations between the eye's blood vessels, nerves, biochemical processes, immune response, genomic, proteomic, and transcriptomic profiles with major organ systems including the kidney, heart, blood system, brain, spinal cord, and liver.
The article comprehensively summarizes the physiological basis of eye examinations in diagnosing systemic diseases, common ophthalmic imaging modalities, and AI technologies related to ophthalmic image analysis. It also explores the research and application of these AI technologies in various systemic diseases. Furthermore, the paper delves into the current challenges faced in this field and the prospects for future development.
The review outlines two primary modes of ocular image analysis: one is the end-to-end AI approach, which learns from massive image data to develop auxiliary screening and diagnostic models for systemic diseases; the other is performing feature engineering based on prior medical knowledge and modeling with traditional machine learning methods to develop more interpretable AI models.
In summary, AI systems based on ophthalmic imaging have shown unprecedented potential in diagnosing systemic diseases, and future research needs to delve into how to extract undiscovered clinical information from ophthalmic AI models and explore effective ways to translate these technologies into clinical practice.: Progress in the diagnosis of systemic diseases based on ophthalmic imaging artificial intelligence technology retrieved 22 March 2024 from https://medicalxpress.
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