Goals of this webinar:

To describe the relationship between artificial intelligence (AI), machine learning (ML), and deep learning (DL).
To describe general scenarios when ML is appropriate.
To understand methods for comparing the performance of different ML algorithms
To layout general criteria to examine when evaluating literature that includes machine learning algorithms

Presented by:

Laura Saba, PhD
Associate Professor
Department of Pharmaceutical Sciences
Skaggs School of Pharmacy and Pharmaceutical Sciences
University of Colorado Anschutz Medical Campus
Aurora, CO

lecture slides

References

Liu Y, Chen PC, Krause J, Peng L. How to Read Articles That Use Machine Learning: Users' Guides to the Medical Literature. JAMA. 2019 Nov 12;322(18):1806-1816. doi: 10.1001/jama.2019.16489. PMID: 31714992.

Rajkomar A, Dean J, Kohane I. Machine Learning in Medicine. N Engl J Med. 2019 Apr 4;380(14):1347-1358. doi: 10.1056/NEJMra1814259. PMID: 30943338.

Libbrecht MW, Noble WS. Machine learning applications in genetics and genomics. Nat Rev Genet. 2015 Jun;16(6):321-32. doi: 10.1038/nrg3920. Epub 2015 May 7. PMID: 25948244; PMCID: PMC5204302.

Guide to evaluating the application of machine learning methods in genetics literature

References

Other Links Referenced During Discussion