The Application of Artificial Intelligence in the Analysis of Biomarkers for Diagnosis and Management of Uveitis and Uveal Melanoma: A Systematic Review - Bassi A; Krance SH; Pucchio A; Pur DR; Miranda RN; Felfeli T (Clinical Ophthalmology, 2022)
Arshpreet Bassi,1 Saffire H Krance,1 Aidan Pucchio,2 Daiana R Pur,1 Rafael N Miranda,3,4 Tina Felfeli3– 5 1Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada; 2School of Medicine, Queen’s University, Kingston, Ontario, Canada; 3Toronto Health Economics and Technology Assessment Collaborative, Toronto, Ontario, Canada; 4The Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; 5Department of Ophthalmology and Visual Sciences, University of Toronto, Toronto, Ontario, CanadaCorrespondence: Tina Felfeli, Department of Ophthalmology and Visual Sciences, University of Toronto, 340 College Street, Suite 400, Toronto, ON M5T 3A9, Canada, Fax +416-978-4590, Email tina.felfeli@mail.utoronto.caPurpose: This study aims to identify the available literature describing the utilization of artificial intelligence (AI) as a clinical tool in uveal diseases.Methods: A comprehensive literature search was conducted in 5 electronic databases, finding studies relating to AI and uveal diseases.Results: After screening 10,258 studies,18 studies met the inclusion criteria. Uveal melanoma (44%) and uveitis (56%) were the two uveal diseases examined. Ten studies (56%) used complex AI, while 13 studies (72%) used regression methods. Lactate dehydrogenase (LDH), found in 50% of studies concerning uveal melanoma, was the only biomarker that overlapped in multiple studies. However, 94% of studies highlighted that the biomarkers of interest were significant.Conclusion: This study highlights the value of using complex and simple AI tools as a clinical tool in uveal diseases. Particularly, complex AI methods can be used to weigh the merit of significant biomarkers, such as LDH, in order to create staging tools and predict treatment outcomes.Keywords: uveal melanoma, uveitis, artificial intelligence, biomarkers