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 ResourceFoundations of Artificial Intelligence
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
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
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
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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