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Explore the introduction and clinical challenges of cancer in this informative lecture by Sudha Sundar. Gain insights into the complexities of cancer diagnosis, treatment, and management as part of the "Machine Learning for Health and Disease" program. Delve into the intersection of machine learning, statistics, and clinical practice in oncology. Learn how modern computational techniques can be applied to better understand and analyze health-related data in cancer care. Discover the potential of machine learning in predicting patient outcomes, analyzing medical imaging, and interpreting genomic data. Understand the importance of bridging the gap between mathematical modeling and clinical problems in cancer research and treatment. Suitable for PhD students in STEM fields, medical students, postdoctoral fellows, faculty, and professionals in science, engineering, and medicine interested in the application of machine learning to oncology.
