{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11983868","patent":{"patent_number":"US-11983868","title":"Predicting neo-adjuvant chemotherapy response from pre-treatment breast magnetic resonance imaging using artificial intelligence and HER2 status","assignee":null,"inventors":[],"filing_date":"2019-02-20T00:00:00.000Z","publication_date":"2024-05-14T00:00:00.000Z","cpc_codes":["G06T","G06F","G06F","G06T","G06V","G06V","G06V","G06V","G16B","G16B","G16B","G16H","G16H","G16H","G06T","G06T","G06T","G06T","G06V"],"num_claims":20,"abstract":"Embodiments predict response to neoadjuvant chemotherapy (NAC) in breast cancer (BCa) from pre-treatment dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Embodiments compute, using a machine learning (ML) classifier, a first probability of response based on a set of radiomic features extracted from a tumoral region represented in a pre-treatment DCE-MRI image of a region of tissue (ROT) demonstrating BCa; extract patches from the tumoral region; provide the patches to a convolutional neural network (CNN); receive, from the CNN, a pixel-level localized patch probability of response; compute a second probability of response based on the pixel-level localized patch probability; compute a combined ML probability from the first and second probabilities; compute a final probability of response based on the combined ML probability and clinical information associated with the ROT; classify the ROT as a responder or non-responder based on the final probability of response; and display the classification."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Predicting neo-adjuvant chemotherapy response from pre-treatment breast magnetic resonance imaging using artificial intelligence and HER2 status","description":"Embodiments predict response to neoadjuvant chemotherapy (NAC) in breast cancer (BCa) from pre-treatment dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Embodiments compute, using a ma","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11983868","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11983868","citation_suggestion":"Patentable. \"Predicting neo-adjuvant chemotherapy response from pre-treatment breast magnetic resonance imaging using artificial intelligence and HER2 status\" (US-11983868). https://patentable.app/patents/US-11983868","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11983868","json":"https://patentable.app/api/llm-context/US-11983868","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T05:04:33.311Z"}