TIGP (BIO)—Machine Learning for Oncology Care Management from risk assessment, diagnostic support, to treatment selection and development

Abstract

Despite the public health emphasis on population-level cancer screening in recent decades, adherence remains lower than desired, and cancer is often detected too late for successful treatment. In this talk, we will review cancer signals extracted from blood, present the integration of multiomics signals in Machine Learning models, and understand the impact of early cancer detection. In addition to diagnostic support, we will also discuss the opportunities and challenges of Machine Learning in the wide range of Oncology care management including treatment selection and drug development.

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