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Broad Institute Inc machine learning algorithm
Machine Learning Algorithm, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/machine+learning+algorithm/machine+learning+algorithms/pmc08699145__mmc3-1-145-149
Average 90 stars, based on 1 article reviews
machine learning algorithm - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Machine learning enables new insights into genetic contributions to liver fat accumulation
Article Snippet: They identify common and rare genetic variants influencing liver fat and demonstrate utility for epidemiological studies. ll OPEN ACCESS ll Article Machine learning enables new insights into genetic contributions to liver fat accumulation Mary E. Haas,1,2,12 James P. Pirruccello,1,4,5,6,12 Samuel N. Friedman,6,12 Minxian Wang,1 Connor A. Emdin,1,4 Veeral H. Ajmera,7 Tracey G. Simon,4,8 Julian R. Homburger,9 Xiuqing Guo,11 Matthew Budoff,11 Kathleen E. Corey,4,8 Alicia Y. Zhou,9 Anthony Philippakis,6,10 Patrick T. Ellinor,1,4,5,6 Rohit Loomba,7 Puneet Batra,6 and Amit V. Khera1,3,4,5,6,13,* 1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA 2Department of Molecular Biology, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA 3Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA 4Department of Medicine, Harvard Medical School, Boston, MA 02114, USA 5Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA 6Machine Learning for Health, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA 7NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA 92103, USA 8Liver Center, Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA 9Color Health, Burlingame, CA 94010, USA 10Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA 11The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA 12These authors contributed equally 13Lead contact *Correspondence: avkhera@mgh.harvard.edu https://doi.org/10.1016/j.xgen.2021.100066 SUMMARY Excess liver fat, called hepatic steatosis, is a leading risk factor for end-stage liver disease and cardiometabolic diseases but often remains undiagnosed in clinical practice because of the need for direct imaging assessments.

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Article Title: Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management
Article Snippet: Applying artificial intelligence to materials research requires abundant curated experimental data and the ability for algorithms to request new experiments.. ESCALATE (Experiment Specification, Capture and Laboratory Automation Technology)—an ontological framework and opensource software package—solves this problem by providing an abstraction layer for humanand machine-readable experiment specification, comprehensive and extensible (meta-) data capture, and structured data reporting.. ESCALATE simplifies the initial data collection process, and its reporting and experiment generation mechanisms simplify machine learning integration.



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