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Early and accurate detection of FK is essential for effective management. Traditional diagnostic methods are often time\u2010consuming and require specialized laboratory resources. Recently, advances in artificial intelligence and computer vision have enabled automated diagnosis of FK using slit\u2010lamp images. In this article, a comprehensive evaluation of state\u2010of\u2010the\u2010art techniques adopted for classifying FK using in vivo confocal microscopy (IVCM) images is presented. Detailed experiments and performance evaluation of various machine learning models are systematically performed, with a focus on evaluating the effect of diverse techniques for image processing, data augmentation, hyperparameters and model finetuning to assess each model's strengths and limitations. Experiments revealed that applying green channel preprocessing with a 12\u2010feature set achieved 99% accuracy using Random Forest, highlighting its effectiveness in FK detection, while complex techniques like histogram modelling reduced accuracy to 64%. Robust models like AdaBoost and RUSBoost maintained high F1\u2010scores, demonstrating adaptability to imbalanced medical datasets, and to real\u2010world clinical\u00a0scenarios.<\/jats:p>","DOI":"10.1049\/htl2.70051","type":"journal-article","created":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T04:44:25Z","timestamp":1766205865000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Ensemble Machine Learning Approaches for Automated Fungal Keratitis Diagnosis Using In Vivo Confocal Microscopy Images"],"prefix":"10.1049","volume":"12","author":[{"given":"Sowmya Kamath","family":"S.","sequence":"first","affiliation":[{"name":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology, Surathkal Mangaluru Karnataka India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shikha","family":"Reji","sequence":"additional","affiliation":[{"name":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology, Surathkal Mangaluru Karnataka India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vaibhava","family":"Lakshmi","sequence":"additional","affiliation":[{"name":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology, Surathkal Mangaluru Karnataka India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Supreetha","family":"R.","sequence":"additional","affiliation":[{"name":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology, Surathkal Mangaluru Karnataka India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pratiksha","family":"Gawas","sequence":"additional","affiliation":[{"name":"Healthcare Analytics and Language Engineering (HALE) Lab Department of Information Technology National Institute of Technology, Surathkal Mangaluru Karnataka India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8091-5053","authenticated-orcid":false,"given":"Veena","family":"Mayya","sequence":"additional","affiliation":[{"name":"Manipal Institute of Technology, Manipal Academy of Higher Education Manipal Karnataka India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manali","family":"Hazarika","sequence":"additional","affiliation":[{"name":"Cornea, Cataract &amp; Ocular Surface Services Royal Eye Infirmary \u2010 University Hospitals Plymouth NHS Trust Plymouth England"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"265","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/0002\u20109394(88)90705\u20102"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.2147\/OPTH.S447138"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/jof7110907"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpbup.2021.100013"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1504\/IJBET.2023.133723"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489\u2010022\u201003490\u20108"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042\u2010024\u201018624\u2010y"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010025\u201094567\u20100"},{"key":"e_1_2_12_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2808941"},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10792\u2010022\u201002616\u20108"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12061344"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2023.104438"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.3389\/fcimb.2022.860370"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.3390\/app9142789"},{"issue":"3","key":"e_1_2_12_16_1","first-page":"92","article-title":"Automatic Detection of Corneal Ulcer by Machine Learning Algorithms","volume":"16","author":"Susila S. 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