Towards Global AI-Driven Cervical Cancer Screening
The global elimination of cervical cancer is a key public health goal set by the World Health Organization (WHO), with screening programs reducing mortality by up to 80%. However, access to experts and biopsy services is limited in low- to middle-income countries (LMICs). Deep learning (DL)-based algorithms offer promising support for screening, but most existing approaches have been developed and validated on private datasets from single countries. We present the first DL-based approach to cervical cancer screening validated on data from multiple countries. Technically, we phrase the problem of detecting and classifying lesions in colposcopy images as a multi-task learning problem, in wh...
| Authors | Thuy Nuong Tran, Ömer Sümer, Evangelia Christodoulou et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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