GENERATING ELECTRONIC TUMOR MARKER ANALOGS OF CARBOHYDRATE ANTIGEN 19-9 USING MACHINE LEARNING

Electronic tumor marker values are generated from patient health data using a suitably trained machine learning model. In general, the electronic tumor marker data include estimated values of an electronic tumor marker that is analogous or otherwise complementary to carbohydrate antigen 19-9 ("...

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Bibliographic Details
Main Authors THALJI, Sam Z, KOTHARI, Anai N
Format Patent
LanguageEnglish
French
Published 21.03.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
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Summary:Electronic tumor marker values are generated from patient health data using a suitably trained machine learning model. In general, the electronic tumor marker data include estimated values of an electronic tumor marker that is analogous or otherwise complementary to carbohydrate antigen 19-9 ("CA19-9") biomarkers measured from a patient or biological specimen. Des valeurs de marqueur de tumeur électronique sont générées à partir de données de santé de patient à l'aide d'un modèle d'apprentissage automatique entraîné de manière appropriée. En général, les données de marqueur de tumeur électronique comprennent des valeurs estimées d'un marqueur de tumeur électronique qui est analogue ou sinon complémentaire à des biomarqueurs d'antigène carbohydrate 19-9 ("CA19-9") mesurés sur un patient ou un échantillon biologique.
Bibliography:Application Number: WO2023US74508