This 1 week course introduces how artificial intelligence is transforming cancer diagnosis and treatment. Students examine how multi-omics data - the integrated measurement of a patient's genomic, proteomic, and metabolomic profiles - alongside histology, the microscopic analysis of tumor tissue structure, are interpreted by AI systems to personalize cancer care. Through real-world clinical and research case studies, students explore how computational tools identify tumor patterns, predict treatment outcomes, and guide therapeutic decisions across diverse cancer types. No programming or machine learning background required. Designed for students in biology, medicine, data science, bioinformatics, public health, and policy seeking foundational literacy in AI-driven oncology.
1 units · Medical Satisfactory/No Credit
This 1 week course introduces how artificial intelligence is transforming cancer diagnosis and treatment. Students examine how multi-omics data - the integrated measurement of a patient's genomic, proteomic, and metabolomic profiles - alongside histology, the microscopic analysis of tumor tissue structure, are interpreted by AI systems to personalize cancer care. Through real-world clinical and research case studies, students explore how computational tools identify tumor patterns, predict treatment outcomes, and guide therapeutic decisions across diverse cancer types. No programming or machine learning background required. Designed for students in biology, medicine, data science, bioinformatics, public health, and policy seeking foundational literacy in AI-driven oncology.
Offered in Autumn 2026 at Stanford University.