Multicontrast Pocket Colposcopy Cervical Cancer Diagnostic Algorithm for Referral Populations
Objective and Impact Statement. We use deep learning models to classify cervix images—collected with a low-cost, portable Pocket colposcope—with biopsy-confirmed high-grade precancer and cancer. We boost classification performance on a screened-positive population by using a class-balanced loss and...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2022-01-01
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| Series: | BME Frontiers |
| Online Access: | http://dx.doi.org/10.34133/2022/9823184 |