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With the coronavirus wreaking havoc on medical and healthcare systems across the globe, the need for enhanced and better organized healthcare has become more and more apparent. An up and coming solution for this is the use of artificial intelligence (AI) in both general healthcare and ophthalmology.
AI in healthcare has enormous potential in increasing the effectiveness of and improving health screening, diagnosis, and the monitoring of diseases. Artificial intelligence can be used to analyze trends and perform diagnoses, as the AI can learn the trends and patterns and harness data. Using what the AI has studied with its algorithm, healthcare professionals will be able to deliver individualized care to patients with retinal (eye) diseases. Most importantly, AI can help researchers in scientific discovery, and help improve the efficiency and success of clinical trials. Instead of having researchers sift through hours of data, the AI can do it in a fraction of the time, proving that AI has the potential to improve patient care at every stage of the patient journey.
However, AI in healthcare has a long way to go, in which data infrastructure needs to improve, and more powerful AI must be produced. Benchmarks, which are pieces of data that are specific indicators of something (diseases in this case) need to be established, so that the AI can identify diseases such as congenital cataract, glaucoma, or papilledema. Government involvement is crucial to establishing a regulatory framework, so that our use of AI is as ethical as possible; no data privacy concerns will be breached. Likewise, it will require widespread collaboration between healthcare professionals, the tech industry, the economic sector, and the government in order to ensure safe deployment. The tools that are used must be clinically validated, in order to leverage the ability of AI to deeply analyze data and to interpret the recommendations of the AI in a clinical setting. By being able to analyze so much more of each individual's data and by using AI recommendations, medical providers are now able to make informed decisions in personalized medicine, This will ultimately help to transform healthcare and lead ophthalmology in a more personalized direction.
As with all healthcare and scientific discovery, accessibility must be considered. AI is expensive to implement and to use, and with the already apparent disparities between healthcare in impoverished areas versus affluent areas in Canada alone, we need to consider the possibility that this technology will further widen the economic gap in areas that have high rates of poverty as well as rural areas and areas that are more wealthy. With the help of organizations like World in Focus, who aim to reduce the healthcare inequities that exist in our world and increase the availability of ophthalmology, perhaps this groundbreaking AI technology can be made accessible to everyone and drive healthcare in a positive direction.
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