Role of artificial intelligence in determining factors impacting patients’ refractive surgery decisions

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dc.contributor.authorKundu, Gairiken_US
dc.contributor.authorVirani, Imranalien_US
dc.contributor.authorShetty, Rohiten_US
dc.contributor.authorKhamar, Poojaen_US
dc.contributor.authorNuijts, Rudy M M Aen_US
dc.date.accessioned2023-08-25T06:36:24Z
dc.date.available2023-08-25T06:36:24Z
dc.date.issued2023-03
dc.description.abstractPurpose: To create a predictive model using artificial intelligence (AI) and assess if available data from patients’ registration records can help in predicting definitive endpoints such as the probability of patients signing up for refractive surgery. Methods: This was a retrospective analysis. Electronic health records data of 423 patients presenting to the refractive surgery department were incorporated into models using multivariable logistic regression, decision trees classifier, and random forest (RF). Mean area under the receiver operating characteristic curve (ROC?AUC), sensitivity (Se), specificity (Sp), classification accuracy, precision, recall, and F1?score were calculated for each model to evaluate performance. Results: The RF classifier provided the best output among the various models, and the top variables identified in this study by the RF classifier excluding income were insurance, time spent in the clinic, age, occupation, residence, source of referral, and so on. About 93% of the cases that did undergo refractive surgery were correctly predicted as having undergone refractive surgery. The AI model achieved an ROC?AUC of 0.945 with an Se of 88% and Sp of 92.5%. Conclusion: This study demonstrated the importance of stratification and identifying various factors using an AI model which could impact patients’ decisions while selecting a refractive surgery. Eye centers can build specialized prediction profiles across disease categories and may allow for the identification of prospective obstacles in the patient’s decision?making process, as well as strategies for dealing with them.en_US
dc.identifier.affiliationsDepartment of Cornea and Refractive Surgery, Narayana Nethralaya, Bangalore, Karnataka, Indiaen_US
dc.identifier.affiliationsDepartment of Refractive Sales, Carl Zeiss Meditec AG, Germanyen_US
dc.identifier.affiliationsDepartment of Cataract and Refractive Surgery, Narayana Nethralaya, Bangalore, Karnataka, Indiaen_US
dc.identifier.affiliationsDepartment of Ophthalmology, Maastricht University Medical Center, Maastricht, The Netherlanden_US
dc.identifier.citationKundu Gairik, Virani Imranali, Shetty Rohit, Khamar Pooja, Nuijts Rudy M M A. Role of artificial intelligence in determining factors impacting patients’ refractive surgery decisions. Indian Journal of Ophthalmology. 2023 Mar; 71(3): 810-817en_US
dc.identifier.issn1998-3689
dc.identifier.issn0301-4738
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/224881
dc.languageenen_US
dc.publisherAll India Ophthalmological Societyen_US
dc.relation.issuenumber3en_US
dc.relation.volume71en_US
dc.source.urihttps://doi.org/10.4103/IJO.IJO_2718_22en_US
dc.subjectArtificial intelligenceen_US
dc.subjectmachine learningen_US
dc.subjectophthalmologic surgical proceduresen_US
dc.subjectpredictive analysisen_US
dc.titleRole of artificial intelligence in determining factors impacting patients’ refractive surgery decisionsen_US
dc.typeJournal Articleen_US
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