In the field of ophthalmology, the integration of artificial intelligence (AI) has witnessed significant advances that promise to reshape medical decision-making. Historically characterised by reliance on anecdotal evidence and limited clinical assessments, the emergence of large datasets and AI technologies has opened new avenues for optimisation and validation of medical practices.
AI's growing presence in ophthalmology, particularly in screening and diagnosing diseases such as glaucoma, diabetic retinopathy, macular degeneration, cataracts, and keratoconus, stems from progress made over the past decade. Uday Devgan, MD, and his colleagues at Advanced Euclidean Solutions, believe that AI can transcend traditional predictive capabilities to guide physicians in producing superior health outcomes. In an interview, Dr Devgan stated, "Our vision back then was that AI can do more than only predict something, but rather it can take it one step further to guide the next step and continually improve in perpetuity.”
The company's recent initiatives have led to the development of innovative methodology for improving intraocular lens (IOL) calculations, culminating in the awarding of a U.S. patent. The patent concerns a virtual, cloud-based tool designed to refine refractive outcomes based on data accumulated from various surgical practices. Dr Devgan, along with Dr Albert Jun and Dr John Ladas, emphasised that their work aims to secure a comprehensive adjustment capability for surgical IOL decisions, enabling the refinement of variables such as axial length, corneal power, lens thickness, and anterior chamber depth.
Traditionally, ophthalmic surgeons have adjusted A-constants to enhance surgical results, relying on historical data and individual postoperative results. However, this practice has become outdated, as it has been determined that uniform adjustments do not adequately account for the uniqueness of individual anatomical features. The researchers advocate for a method that incorporates a multitude of variables and can evolve with advancements in understanding and technology.
Notably, the algorithms used for such refinements are increasingly sophisticated, benefiting from the advancements in computational capabilities afforded by large language models. This allows for extensive automation in the adjustment of formulas that underpin refractive surgeries, a move away from a one-size-fits-all methodology.
The future of AI in ophthalmology appears promising, with additional patents in the pipeline that aim to leverage deep learning and historical outcomes to inform treatment strategies. Their work extends beyond IOL calculations to encompass predictions of treatment outcomes in retinal interventions, employing self-optimising algorithms that adapt to new modalities.
Dr Devgan encapsulates the ongoing transformation of the field, suggesting that we are currently at a pivotal point in medicine. He states, “We believed 10 years ago and now more than ever that this is a pathway to better outcomes in all fields of medicine, especially ophthalmology.” As AI technologies continue to develop, the expectation is that they will fundamentally reshape clinical practices, leading to more precise and effective patient care.
Source: Noah Wire Services