{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11972867","patent":{"patent_number":"US-11972867","title":"Method of training a machine learning data processing model, method of determining a hypoxia status of a neoplasm in a human or animal body, and system therefore","assignee":null,"inventors":[],"filing_date":"2020-12-16T00:00:00.000Z","publication_date":"2024-04-30T00:00:00.000Z","cpc_codes":["G16H","G06N","G06N","G06T","G16H","G16H","G16H","G06T","G06T"],"num_claims":20,"abstract":"The present document describes a training method of a machine learning data processing model for determining a hypoxia status of a neoplasm, in particular a random forest model. The method comprises obtaining, for a plurality of neoplasms, at least one data sample comprising 3D imaging data. A hypoxic volume fraction is determined for each data sample, as well as a set of image features associated with the neoplasm. The method further iterates a sequence of training steps and each iteration includes: selecting a subset of image features and eliminating, for each data sample, the subset of image features to yield a reduced set of image features. The iteration also includes generating decision trees, providing a momentary random forest model based thereon, and submitting a test set of image features to the momentary random forest model to yield a performance value. The iterations are continued until all image features have been selected for a subset at least once, and then a plurality of preferred image features are selected for providing a radiomics feature signature. The trained random forest data processing model based on decision trees associated with the preferred image features of the radiomics feature signature."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Method of training a machine learning data processing model, method of determining a hypoxia status of a neoplasm in a human or animal body, and system therefore","description":"The present document describes a training method of a machine learning data processing model for determining a hypoxia status of a neoplasm, in particular a random forest model. The method comprises o","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11972867","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-11972867","citation_suggestion":"Patentable. \"Method of training a machine learning data processing model, method of determining a hypoxia status of a neoplasm in a human or animal body, and system therefore\" (US-11972867). https://patentable.app/patents/US-11972867","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11972867","json":"https://patentable.app/api/llm-context/US-11972867","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T16:14:47.220Z"}