An Approach to Predict Intraocular Diseases by Machine Learning Based on Vitreous Humor Immune Mediator Profile.

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Bibliographic Details
Title: An Approach to Predict Intraocular Diseases by Machine Learning Based on Vitreous Humor Immune Mediator Profile.
Authors: Sugawara R; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Usui Y; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Saito A; Department of AI Applied Quantitative Clinical Science, Tokyo Medical University, Tokyo, Japan., Nezu N; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Komatsu H; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Tsubota K; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Asakage M; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Yamakawa N; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Wakabayashi Y; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan., Sugimoto M; Research and Development Center for Minimally Invasive Therapies, Institute of Medical Science, Tokyo Medical University, Tokyo, Japan., Kuroda M; Department of Molecular Pathology, Tokyo Medical University, Tokyo, Japan., Goto H; Department of Ophthalmology, Tokyo Medical University Hospital, Tokyo, Japan.
Source: Investigative ophthalmology & visual science [Invest Ophthalmol Vis Sci] 2025 Mar 03; Vol. 66 (3), pp. 38.
Publication Type: Journal Article
Journal Info: Publisher: Association For Research In Vision And Ophthalmology (Arvo) Country of Publication: United States NLM ID: 7703701 Publication Model: Print Cited Medium: Internet ISSN: 1552-5783 (Electronic) Linking ISSN: 01460404 NLM ISO Abbreviation: Invest Ophthalmol Vis Sci Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1552-5783
DOI:10.1167/iovs.66.3.38