System and method for predicting the risk of future lung cancer

Risk prediction models are trained and deployed to analyze images, such as computed tomography scans, for predicting future risk of lung cancer for one or more subjects. Individual risk prediction models are separately trained on nodule-specific and non-nodule specific features such that each risk p...

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Bibliographische Detailangaben
Hauptverfasser:	WASHKO, JR, ESTEPAR, RAUL SAN JOSE, STEVENSON, CHRISTOPHER SCOTT, ASH, SAMUEL YOFFE, MAILMAN, MATTHEW DAVID
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING COMPUTING COUNTING HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS
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Beschreibung
Zusammenfassung:	Risk prediction models are trained and deployed to analyze images, such as computed tomography scans, for predicting future risk of lung cancer for one or more subjects. Individual risk prediction models are separately trained on nodule-specific and non-nodule specific features such that each risk prediction model can predict future risk of lung cancer across different time periods (e.g., 1 year, 3 years, or 5 years). Such risk prediction models are useful for developing preventive therapies for lung cancer by enabling clinical trial enrichment.