Stratified Multisource Optical Coherence Tomography Integration and Cross-Pathology Validation Framework for Automated Retinal Diagnostics

Stratified Multisource Optical Coherence Tomography Integration and Cross-Pathology Validation Framework for Automated Retinal Diagnostics

This study presents a clinical utility-driven machine learning framework for retinal Optical Coherence Tomography classification, addressing challenges posed by manual interpretation variability and dataset heterogeneity. The methodology integrates biomimetic data partitioning, deep biomarker extrac...

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Bibliographic Details
Main Authors: Michael Sher, Riah Sharma, David Remyes, Daniel Nasef, Demarcus Nasef, Milan Toma
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Applied Sciences
Subjects:
retinal OCT classification
machine learning
clinical utility
SMOTE optimization
logistic regression
Online Access:https://www.mdpi.com/2076-3417/15/9/4985
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