Data science, human intelligence, and therapeutics discovery: An interview with Sean Escola, Saul Kato, and Pavan Ramkumar.
| Autor: | Ramkumar P; Herophilus, Inc, San Francisco, CA 94107, USA., Kato S; Herophilus, Inc, San Francisco, CA 94107, USA.; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA., Escola GS; Herophilus, Inc, San Francisco, CA 94107, USA.; Zuckerman Institute, Department of Psychiatry, Columbia University, New York City, NY 10032, USA. |
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| Jazyk: | angličtina |
| Zdroj: | Patterns (New York, N.Y.) [Patterns (N Y)] 2022 Apr 08; Vol. 3 (4), pp. 100490. Date of Electronic Publication: 2022 Apr 08 (Print Publication: 2022). |
| DOI: | 10.1016/j.patter.2022.100490 |
| Abstrakt: | Sean Escola, Saul Kato, and Pavan Ramkumar explain the importance of data science in their research. They have developed a simple non-parametric statistical method called the Rank-to-Group (RTG) score that identifies hierarchical confounder effects in raw data and machine learning-derived data embeddings. This approach should be generally useful in experiment-analysis cycles and to ensure confounder robustness in machine learning models. (© 2022 The Authors.) |
| Databáze: | MEDLINE |
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