肺癌查中的AI身体组成:超越肺癌检测的附加值

Kaiwen Xu¹, Mirza S Khan¹, Thomas Z Li¹+8

• ¹From the Department of Computer Science (K.X., Y.H., T.A.L., B.A.L.), Department of Biomedical Engineering (T.Z.L., B.A.L.), School of Medicine (T.Z.L.), and Department of Electrical and Computer Engineering (Y.H., B.A.L.), Vanderbilt University, 2301 Vanderbilt Pl, Nashville, TN 37235; University of Missouri-Kansas City, Kansas City, Mo (M.S.K.); Saint Luke's Mid America Heart Institute, Kansas City, Mo (M.S.K.); Siemens Healthineers, Princeton, NJ (R.G.); Department of Radiology (J.G.T., J.J.C., B.A.L., K.L.S.), Department of Biomedical Informatics (T.A.L., J.J.C., B.A.L.), Division of Cardiovascular Medicine (J.J.C.), Division of Allergy, Pulmonary and Critical Care Medicine (F.M.), Vanderbilt University Institute of Imaging Science (B.A.L.), Vanderbilt Brain Institute (B.A.L.), Department of Psychiatry and Behavioral Sciences (B.A.L.), Department of Neurology (B.A.L.), and Vanderbilt Memory & Alzheimer's Center (B.A.L.), Vanderbilt University Medical Center, Nashville, Tenn.