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

MLA

Cosentino, Justin, et al. “Inference of Chronic Obstructive Pulmonary Disease with Deep Learning on Raw Spirograms Identifies New Genetic Loci and Improves Risk Models.” Nature Genetics, vol. 55, no. 5, May 2023, pp. 787–95. EBSCOhost, https://doi.org/10.1038/s41588-023-01372-4.

APA

Cosentino, J., Behsaz, B., Alipanahi, B., McCaw, Z. R., Hill, D., Schwantes-An, T.-H., Lai, D., Carroll, A., Hobbs, B. D., Cho, M. H., McLean, C. Y., & Hormozdiari, F. (2023). Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models. Nature Genetics, 55(5), 787–795. https://doi.org/10.1038/s41588-023-01372-4

Chicago

Cosentino, Justin, Babak Behsaz, Babak Alipanahi, Zachary R. McCaw, Davin Hill, Tae-Hwi Schwantes-An, Dongbing Lai, et al. 2023. “Inference of Chronic Obstructive Pulmonary Disease with Deep Learning on Raw Spirograms Identifies New Genetic Loci and Improves Risk Models.” Nature Genetics 55 (5): 787–95. doi:10.1038/s41588-023-01372-4.