This video is intended to give students (high school, undergrad, and grad) as well as new staff, an overview of some of the basic information regarding what scientific research involves including: the scientific method, conducting a literature search, the anatomy of primary source articles, scientific communication, the publishing process, broad goals of research labs, how to make a useful contributions to a research lab, and more.
View ResourceArtificial Intelligence Course (Health-AI)
February 19, 2026
by
Elizabeth
Educational lectures developed by Dr. Ryan Urbanowicz in 2026. 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.
View ResourceFoundations of Artificial Intelligence
March 5, 2023
by
Ray
Educational lectures for the course: “Foundations of Artificial Intelligence” developed by Dr. Ryan Urbanowicz in 2020 at the University of Pennsylvania’s Perelman School of Medicine. This is the first of three courses covering topics in artificial intelligence for application within the context of informatics and biomedical research. The course is divided into modules that cover (1) introductory/background materials, (2) logic, (3) other knowledge representation, (4) essentials of expert systems, (5) search, (6) uncertainty, and (7) advanced/auxiliary topics. These topics offer a global foundation for branches of AI application and research, including concepts that will later support a deeper understanding of inductive reasoning and machine learning. In a practical sense, this course focuses on how biomedical data can be organized, represented, interpreted, searched, and applied in order to derive knowledge, make decisions, and ultimately make predictions while avoiding bias. This course was assembled using content from a wide variety of textbooks, slides, and lectures by various authors and speakers on the relevant topics. Some lectures were prepared and given by guest lecturers and thus have not been posted. At the time of posting, this course is in its second year so any feedback is welcome regarding any mistakes or suggested improvements.
View ResourceIntroduction to Research in a Computational Lab
March 5, 2023
by
Ray
This video is intended to give students (high school, undergrad, and grad) as well as new staff, an overview what research is like in a ‘dry’ or computational laboratory.
View ResourceMachine Learning Essentials for Biomedical Data Science
March 5, 2023
by
Ray
An educational playlist (including 11 videos) covering the key essentials for using machine learning as part of a data science analysis pipeline. While topics are primarily framed around applications in biomedicine, this content is broadly applicable to other domains. This series was prepared at the Cedars Sinai Medical Center in Los Angeles by Dr. Ryan Urbanowicz of the Department of Computational Biomedicine.
View ResourceRule-Based Machine Learning
March 5, 2023
by
Ray
A collection of educational videos focusing on rule-based machine learning and/or the more specific family of ‘learning classifier system’ machine learning algorithms. These algorithms are uniquely able to detect, model, and characterize complex multivariate associations in data while yielding much more interpretable models.
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