This course will explore how AI can be a driving force for automated clinical decision support and medical discovery. We will explore concepts in logic, knowledge representation, expert systems for automated decision-making, search algorithms, uncertainty in reasoning, and other related topics that will enable you to develop, understand, and apply health AI solutions effectively and ethically. We will explore how AI encompasses and differs from machine learning and the distinction between inductive and deductive reasoning. In a practical sense, the course will provide you with the tools to organize, represent, interpret, and search biomedical data to derive knowledge, automate decisions, and make predictions while avoiding bias. This course was developed for the Cedars Sinai Health University graduate programs.
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URBS-Lab with Ryan Urbanowicz
Educational, lecture, how-to, and other videos. On topics including (but not limited to) machine learning, artificial intelligence, data mining, biomedicine, statistics, teaching and more. I run the URBS Lab (Unbounded Research in Biomedical Systems) at the Cedars Sinai Medical Center. My views are my own.
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