Statistics, Bioinformatics, and AI in SABV Research

Übersicht

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

Lehrplan

• Practical Aspects of SABV in Research
In this module, instructors provide an introduction to study sex differences in human research.
• Methodological Considerations for SABV Research
In this module, instructors provide more detail on methods to study sex differences in human research by providing examples for both laboratory and clinical trials.
• Biostatistics and AI in Sex Differences and SABV Research
In this module, instructors provide a basic understanding for the use of ML/AI and biostatistics in sex difference and SABV research.

---

Unterrichtet von

Ludeman Family Center for Women's Health Research

---

Fachgebiete

Science