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Software that reads screening mammograms alongside or before radiologists, catching more cancers and cutting the reading workload in large trials.
Deep-learning readers for mammography have regulatory clearance in Europe and the United States and are being tested as a replacement for one of the two human readers used in European screening programmes. The Swedish MASAI randomised trial found AI-supported screening detected more cancers with a lower reading workload, and the Danish and German programmes have reported similar results in practice. Risk-prediction models from the same images are being studied to personalise screening intervals.
Convolutional networks trained on millions of mammograms produce a suspicion score per breast; low-scoring exams go to single reading and high-scoring ones are flagged for human review or recall.
Nothing in the corpus depends on this yet.
Dependencies are what this technology cannot be delivered without: manufacturing steps, instruments, software, upstream methods. See its full chain on the map.
Query for this technology: (TITLE:"AI-assisted mammography screening" OR ABSTRACT:"AI-assisted mammography screening") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about AI-assisted mammography screening, not a curated reading list.
Shares Mammography & tomosynthesis, HER2-positive breast cancer, Triple-negative breast cancer (TNBC), HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, HER2-positive breast cancer, Triple-negative breast cancer (TNBC), HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, HER2-positive breast cancer, Triple-negative breast cancer (TNBC), HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, HER2-positive breast cancer, Triple-negative breast cancer (TNBC), HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, HER2-positive breast cancer, Triple-negative breast cancer (TNBC), HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, HER2-positive breast cancer, Triple-negative breast cancer (TNBC), HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, HER2-positive breast cancer, Triple-negative breast cancer (TNBC), HR-positive / HER2-negative breast cancer.
Shares Contrast-enhanced mammography, Mammography & tomosynthesis, HR-positive / HER2-negative breast cancer.
Open-source projects that implement or serve this technology, from OnCo's own catalogue: licence and last activity as the repository reported them on the day of the fetch. Listing is not endorsement; check the licence before reuse and the validation before clinical use.
NYU's deep neural network for screening mammography interpretation, with weights and code released.
NYU's globally-aware multiple instance classifier for high-resolution mammograms.
A mammography-based model of five-year breast cancer risk from MIT, validated across several countries.
Containers and scripts to run and compare published mammography AI models on new datasets.