Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.

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Bibliographic Details
Title: Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.
Authors: Cosentino J; Google Health AI, Palo Alto, CA, USA. jtcosentino@google.com., Behsaz B; Google Health AI, Cambridge, MA, USA., Alipanahi B; Google Health AI, Palo Alto, CA, USA., McCaw ZR; Google Health AI, Palo Alto, CA, USA., Hill D; Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA.; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA., Schwantes-An TH; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.; Division of Cardiology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA., Lai D; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA., Carroll A; Google Health AI, Palo Alto, CA, USA., Hobbs BD; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA., Cho MH; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA., McLean CY; Google Health AI, Cambridge, MA, USA., Hormozdiari F; Google Health AI, Cambridge, MA, USA. fhormoz@google.com.
Source: Nature genetics [Nat Genet] 2023 May; Vol. 55 (5), pp. 787-795. Date of Electronic Publication: 2023 Apr 17.
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Nature Pub. Co Country of Publication: United States NLM ID: 9216904 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1546-1718 (Electronic) Linking ISSN: 10614036 NLM ISO Abbreviation: Nat Genet Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1546-1718
DOI:10.1038/s41588-023-01372-4