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Enhancing detection of cervical cancer through deep learning: a comparative study of histological image-based algorithms
Cervical cancer is a significant contributor to cancer-related deaths among women worldwide, especially in low- and middle-income countries (LMICs) where access to screening services is limited. Early detection plays a vital role in improving patient outcomes. However, traditional diagnostic techniq...
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| Format: | Thesis |
| Language: | English English |
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Department of Integrative Biomedical Sciences (IBMS)
2026
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