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Asthma-Neoplasms Relationships: New Insights Using Machine Inference, Epidemiological Reasoning, And Big Data
Abbas Shojaee, Jose L. Gomez, Xiaochen Wang, Naftali Kaminski, Jonathan M. Siner, Seyedtaghi Takyar, Hongyu Zhao, Geoffrey Chupp
doi: https://doi.org/10.1101/439117
Abbas Shojaee
1Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
2Center for Precision Pulmonary Medicine (P2MED), Yale University School of Medicine, New Haven, Connecticut, USA
Jose L. Gomez
1Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
Xiaochen Wang
3Department of Biostatistics, School of Public Health, Yale University, New Haven, Connecticut, USA
Naftali Kaminski
1Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
Jonathan M. Siner
1Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
Seyedtaghi Takyar
1Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
Hongyu Zhao
3Department of Biostatistics, School of Public Health, Yale University, New Haven, Connecticut, USA
Geoffrey Chupp
1Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
Article usage
Posted October 11, 2018.
Asthma-Neoplasms Relationships: New Insights Using Machine Inference, Epidemiological Reasoning, And Big Data
Abbas Shojaee, Jose L. Gomez, Xiaochen Wang, Naftali Kaminski, Jonathan M. Siner, Seyedtaghi Takyar, Hongyu Zhao, Geoffrey Chupp
bioRxiv 439117; doi: https://doi.org/10.1101/439117
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