US12603184B2 - Systems and Methods for Continuous Cancer Treatment and Prognostics
Summary
USPTO granted patent US12603184B2 to The Regents of the University of California on April 14, 2026. The patent covers AI systems for continuous cancer treatment and prognostics, including methods for organizing multimodal health data, assessing data quality, and applying NLP to electronic health records for cancer survival prediction. The patent contains 17 claims and falls under CPC classifications G16H 50/30, G16H 10/60, and related health informatics categories.
What changed
USPTO issued patent US12603184B2 to The Regents of the University of California for a continuously learning oncology infrastructure using AI and natural language processing on electronic health records. The patent covers methods for cancer prognostics, term frequency analysis for survival prediction, and in silico clinical trials based on health record data. Olivier Morin is listed as inventor.
Healthcare providers and AI developers in the oncology space should be aware of this granted intellectual property covering AI-driven cancer treatment systems. While patent grants do not impose compliance obligations, entities developing similar health informatics or cancer prediction AI may need to consider potential licensing implications or design-around strategies to avoid infringement.
Archived snapshot
Apr 17, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
Systems and methods for continuous cancer treatment and prognostics
Grant US12603184B2 Kind: B2 Apr 14, 2026
Assignee
The Regents of the University of California
Inventors
Olivier Morin
Abstract
Oncology faces a digital chasm in its quest for personalized treatments. Despite the adoption of electronic health records (EHR), most hospitals are ill-equipped for data science research. Embodiments herein describe a continuously learning infrastructure through which multimodal health data are systematically organized and data quality is assessed with the goal of applying artificial intelligence to address unmet clinical needs. Embodiments describe systems and methods for improved cancer prognostics, including by obtaining electronic medical records and performing natural language processing thereon. Additional embodiments apply term frequency inverse document frequency to identify terms that are predictive for cancer survival. Additional embodiments are capable of performing in silico clinical trials based on information comprised in a collection of health records.
CPC Classifications
G16H 50/30 G16H 10/60 G16H 50/70 G16H 50/20 G06F 40/216
Filing Date
2022-05-02
Application No.
18557909
Claims
17
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Source
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