mlsanityData to 7 Oct 2026

Pretrained Vision Models for Predicting High-Risk Breast Cancer Stage

arXiv 2303.10730 ↗First posted 19 Mar 2023eess.IV cs.CV cs.LGcited by 1

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Abstract (arXiv)

Cancer is increasingly a global health issue. Seconding cardiovascular diseases, cancers are the second biggest cause of death in the world with millions of people succumbing to the disease every year. According to the World Health Organization (WHO) report, by the end of 2020, more than 7.8 million women have been diagnosed with breast cancer, making it the world's most prevalent cancer. In this paper, using the Nightingale Open Science dataset of digital pathology (breast biopsy) images, we leverage the capabilities of pre-trained computer vision models for the breast cancer stage prediction task. While individual models achieve decent performances, we find out that the predictions of an ensemble model are more efficient, and offer a winning solutionfootnotehttps://www.nightingalescience.org/updates/hbc1-results. We also provide analyses of the results and explore pathways for better interpretability and generalization. Our code is open-source at urlhttps://github.com/bonaventuredossou/nightingalewinningsolution

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 21 of its 27 references that are in the map. First posted on arXiv 19 Mar 2023.

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21 of 27 references.

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