Specific Aim 1) Test AI-CVD components in NLST for prediction of mortality and outcomes.

Specific Aim 2) Develop and test nodule based risk scoring deep learning models for prediction of lung cancer and mortality.

Morteza Naghavi, MDa, Anthony P. Reeves, PhDb, Kyle Atlas, BSa, Chenyu Zhang, MSa, Thomas Atlas, MDc, Claudia Henschke, PhD., MDd, David Yankelevitz, MDd, Matthew J. Budoff, MDe, Dong Li, PhDe, Wenjun Fan, MD, PhDm, Ruilin Yu, MPHn, Andrea Branch, MDd, Ning Ma, PhDd, Sion K. Roy, MDe, Khurram Nasir, M.Df, Sabee Molloi, PhDg, Zahi Fayad, PhDf, Michael V. McConnell, MD, MSEEh, Ioannis Kakadiaris, MDi, Javier Zuelueta, MDd, David J. Maron, MDh, Jagat Narula, MDi, Kim Williams, MDj, Daniel Levy, M.Dk, Nathan D. Wong, PhDl.

a. HeartLung.AI, Houston, TX, 77021
b. Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853
c. Tustin Teleradiology, Tustin, CA 92780
d. Mount Sinai Hospital, New York, NY 10029
e. The Lundquist Institute, Torrance, CA 90502
f. Houston Methodist Hospital, Houston, TX 77030
g. Department of Radiology, University of California Irvine, CA 92697
h. Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305
i. The University of Texas Health Science Center at Houston, TX, 77030
j. University of Louisville, Louisville, KY
k. Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, 20824
l. Heart Disease Prevention Program, Division of Cardiology, University of California Irvine, CA 92697
m. Department of Epidemiology & Biostatistics, University of California Irvine, CA 92697
n. Department of Epidemiology, University of California, Los Angeles, CA 90095