Browsing OU - Dissertations by Subject "Deep learning"
Now showing items 1-3 of 3
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Applying novel machine learning technology to optimize computer-aided detection and diagnosis of medical images
(2021-05-14)The purpose of developing Computer-Aided Detection (CAD) schemes is to assist physicians (i.e., radiologists) in interpreting medical imaging findings and reducing inter-reader variability more accurately. In developing ... -
Novel Computer-Aided Diagnosis Schemes for Radiological Image Analysis
(2022-05-13)The computer-aided diagnosis (CAD) scheme is a powerful tool in assisting clinicians (e.g., radiologists) to interpret medical images more accurately and efficiently. In developing high-performing CAD schemes, classic ... -
Survival Prediction of Pediatric Leukemia under Model Uncertainty
(2024-05)This dissertation addresses critical challenges in survival prediction for pediatric leukemia, particularly Acute Lymphoblastic Leukemia (ALL), by introducing novel predictive models that incorporate Bayesian principles ...