Data science, human intelligence, and therapeutics discovery: An interview with Sean Escola, Saul Kato, and Pavan Ramkumar.
expert_opinion · Level V
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- Record sourced from PubMed, PMID 35465229.
- Also identified by DOI 10.1016/j.patter.2022.100490 and PMC identifier 9023890.
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Abstract
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.