Statistics, Bioinformatics, and AI in SABV Research
About this course
This course addresses statistics, bioinformatics, and machine learning/artificial intelligence in the study of sex differences and SABV research. You'll learn from experts about the following: addressing common statistical errors, describing challenges related to the measurement of peri and postmenopausal women in research, considering methods to control for hormones in research, identifying preclinical models to answer questions regarding sex differences, illustrating the latest uses of machine learning and artificial intelligence. This course is the third of three courses in the Specialization: Sex as a Biological Variable in the Conduct of Research. Experts: Nannette Santoro, MD, University of Colorado Anschutz Kerrie Moreau, PhD, University of Colorado Anschutz Nancy Lane, MD, UC Davis Nina Stachenfeld, PhD, Yale School of Medicine Janet Rich Edwards, ScD, MPH, Harvard University Audrey Hendricks, PhD, University of Colorado Anschutz Carolyn Mazure, PhD, Yale School of Medicine
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What you'll learn
- understand common statistical errors in research
- discuss challenges in measuring peri and postmenopausal women
- evaluate methods to control for hormonal influences
- identify preclinical models for studying sex differences
- apply machine learning and AI in biological research
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