AI Will Touch All Aspects of Eye Care: Here’s How

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Artificial intelligence (AI) seemed like a very futuristic concept just a few, short years ago. Look around you, and you will quickly see the future has certainly arrived. It feels like it happened suddenly, but what may surprise you is the integration of AI into eye care has been happening for the better part of a decade. AI is already playing a role and could continue to transform how we care for patients, how we manage our practices, and how leaning into technology can enrich lives. Smarter, faster, better is the only way to keep up.  

 

As the demands on optometric physicians continue to grow exponentially, learning where and how to employ AI will help with the burgeoning need of increased productivity. Currently, AI happens in a number of ways across a variety of different channels.  

 

Earlier disease detection, precision medicine, cost efficiencies, educational improvement, and drug development are all sectors that could be augmented with the help of AI. These advancements hold the potential to revolutionize patient outcomes and reshape the way care is delivered and managed, effectively.  

 

Earlier Disease Detection and Real-Time Decision Support

Machine vision and algorithmic improvements are redefining the scope of disease detection. AI-powered imaging tools, such as those using deep learning models, can analyze retinal scans, optical coherence tomography (OCT) images, and other diagnostic modalities with remarkable precision. These systems excel at identifying early signs of diseases such as diabetic retinopathy, glaucoma, and age-related macular degeneration — conditions that might be missed without leveraging this technology.

 

Real-time decision support systems are enhancing clinicians’ ability to make timely and accurate diagnoses. By integrating patient data and culminating that data into an AI model, the data can be reviewed and acted upon in a much more efficient and consistent way. Think of the dry eye patient. Having a tool that will collect symptoms, alongside all of the clinical findings (osmolarity, staining, tear meniscus height, tear break up time, meibomian gland function, blink quality, interferometry, eyelid assessment) gives you that data in real time to compare to a normative database AND each time you make a change in the patients treatment pattern. Would that save precious clinic time? Would that help with diagnosing and managing the patient? Would having that information at your fingertips enable you to give a personalized treatment plan to that patient? These types of tools provide clinicians with actionable insights, enabling personalized care plans. 

 

Precision Medicine and Personalized Treatments

AI is paving the way for precision medicine in eye care, focusing on individualized treatment strategies that optimize outcomes. The convergence of AI with genomic data analysis allows for a more profound understanding of the genetic underpinnings of ocular diseases. For instance, AI algorithms can analyze genetic variations to predict a patient’s response to specific medications, thus minimizing trial-and-error approaches in treatment.  

 

Personalized treatments are particularly impactful in managing chronic conditions such as glaucoma, where patient-specific factors such as intraocular pressure, corneal thickness, and genetic predisposition influence disease progression. By tailoring interventions to these unique parameters, clinicians can enhance therapeutic efficacy while minimizing adverse effects. In cases like refractive surgery, AI can recommend customized surgical plans based on corneal topography and visual needs, ensuring better outcomes and patient satisfaction.

 

Cost Efficiency through AI-Enabled Screening and Streamlined Operations

The rising costs of health care present a significant challenge, and AI offers solutions by enhancing both operational efficiency and clinical accuracy. 

 

Operationally, AI is streamlining administrative processes, such as appointment scheduling, insurance verification, and patient follow-ups. Chatbots and virtual assistants are handling routine inquiries, enabling staff to focus on higher-value tasks. Additionally, AI-driven insights into clinic workflows can identify bottlenecks, improving patient flow and satisfaction. AI can also help problem solve issues and can streamline work so that your people can be more engaged in strategic activities instead of being bogged down by repetitive tasks. AI does what AI can do, and humans can do what only humans can do.  

 

The reduction of clinical errors is another critical area where AI is proving transformative. Automated systems can flag potential prescription errors, ensure adherence to clinical guidelines, and monitor patient progress, reducing the risk of complications. Collectively, these improvements lead to significant cost savings for both providers and patients.

 

Transforming Education in Eye Care

AI is revolutionizing education at multiple levels, for both the patient and the practitioner. Real-time multimedia tools powered by AI are enhancing patient education, making complex medical information accessible and understandable. Interactive visualizations of diseases, treatment pathways, and surgical procedures empower patients to make informed decisions about their care.

 

For ECP’s, AI-driven virtual training platforms offer immersive learning experiences. Simulations of surgeries and diagnostic challenges allow trainees to hone their skills in a risk-free environment, accelerating proficiency and confidence. Moreover, AI algorithms can assess trainees’ performance and provide personalized feedback, ensuring continuous improvement.

 

Accelerating Drug Development and Addressing Treatment Gaps

AI is playing a pivotal role in identifying gaps in current treatments and expediting drug development. Currently it takes 8-12 years and around $500 million to take a drug from bench to bedside. By analyzing vast datasets from clinical trials, patient records, and scientific literature, AI can uncover unmet needs and suggest novel therapeutic targets. This capability is particularly relevant in tackling complex and rare ocular diseases for which effective treatments are limited.

 

The speed and specificity of drug development have also increased with AI-enabled modeling and simulation tools. These technologies can predict how a drug interacts with biological systems, reducing the time and cost of preclinical studies. One example is how AI has facilitated the development of therapies targeting retinal diseases, such as gene therapies and regenerative treatments, by identifying molecular pathways critical to disease progression.

 

The integration of AI into eye care is ushering in a new era of innovation and excellence. The ability to augment clinical experience and produce a better, smarter, faster outcome is the way of the future. From early disease detection and personalized treatments to cost efficiency and transformative education, AI is reshaping the landscape of vision care. Its impact on drug development and treatment optimization further underscores its potential to address longstanding challenges in the field. As these technologies continue to evolve, they promise to enhance patient outcomes, reduce health care disparities, and set new standards for quality and efficiency in eye care. 

Author

  • Selina McGee, OD, FAAO, Dipl ABO

    Dr. Selina McGee is the Visionary Founder and Owner of BeSpoke Vision, a private practice that offers patients a wide range of optometric care via its dry eye center, specialty contact lens clinic and aesthetics suite. She is a renowned national and international speaker. She is an Adjunct Assistant Professor at the Northeastern State University College of Optometry. She is on faculty at The Oklahoma Medical Research Foundation. She currently serves as President for the Intrepid Eye Society and the Secretary of the Board of Examiners in Oklahoma. She is a Fellow of the American Academy of Optometry and a Diplomate of the American Board of Optometry, and is Past-President of the Oklahoma Association of Optometric Physicians and Past-Trustee on the SECO Board. Most recently she was named OD of the South and OD of the year in OK. She is the Co-Medical Editor of Modern Optometry and Associate Editor of Presbyopia and the Aging Eye. She earned her Bachelor of Science in Biology (where she graduated Summa Cum Laude) and Doctor of Optometry (also Summa Cum Laude) from Northeastern State University Oklahoma College of Optometry.



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