Opportunistic Assessment of Ischemic Heart Disease Risk Using Abdominopelvic Computed Tomography and Medical Record Data: a Multimodal Explainable Artificial Intelligence Approach

Autor: Chaudhari As, Robert D. Boutin, Andrew L. Wentland, Sandhu At, Fatima Rodriguez, Bhavik N. Patel, Zambrano Chaves Jm, Jeffrey Rb, Imon Banerjee, David J. Maron, Daniel L. Rubin

Current risk scores for predicting ischemic heart disease (IHD) risk—the leading cause of global mortality—have limited efficacy. While body composition (BC) imaging biomarkers derived from abdominopelvic computed tomography (CT) correlate with I

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::69bb9cd5208a512144b6c9174fbb315e
https://doi.org/10.1101/2021.01.23.21250197

A vision-language foundation model for the generation of realistic chest X-ray images.

Autor: Bluethgen C; Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Palo Alto, CA, USA. bluethgen@stanford.edu.; Department of Radiology, Stanford University, Palo Alto, CA, USA. bluethgen@stanford.edu.; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland. bluethgen@stanford.edu., Chambon P; Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Palo Alto, CA, USA.; Department of Radiology, Stanford University, Palo Alto, CA, USA., Delbrouck JB; Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Palo Alto, CA, USA.; Department of Radiology, Stanford University, Palo Alto, CA, USA., van der Sluijs R; Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Palo Alto, CA, USA.; Department of Radiology, Stanford University, Palo Alto, CA, USA., Połacin M; Department of Radiology, Stanford University, Palo Alto, CA, USA.; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland., Zambrano Chaves JM; Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Palo Alto, CA, USA.; Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA., Abraham TM; University of California, Davis, Davis, CA, USA.; MedARC, Stability AI, London, UK., Purohit S; MedARC, Stability AI, London, UK., Langlotz CP; Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Palo Alto, CA, USA.; Department of Radiology, Stanford University, Palo Alto, CA, USA.; Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA., Chaudhari AS; Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Palo Alto, CA, USA.; Department of Radiology, Stanford University, Palo Alto, CA, USA.; Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA.

Publikováno v: Nature biomedical engineering [Nat Biomed Eng] 2024 Aug 26. Date of Electronic Publication: 2024 Aug 26.

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach.

Autor: Zambrano Chaves JM; Department of Biomedical Data Science, Stanford University, 1265 Welch Road, MSOB West Wing, Third Floor, Stanford, CA, 94305, USA., Wentland AL; Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI, 53792, USA., Desai AD; Department of Radiology, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA.; Department of Electrical Engineering, Stanford University, 350 Jane Stanford Way, Stanford, CA, 94305, USA., Banerjee I; Department of Radiology, Mayo Clinic, 13400 East Shea Blvd, Scottsdale, AZ, 85259, USA., Kaur G; Department of Radiology, Mayo Clinic, 13400 East Shea Blvd, Scottsdale, AZ, 85259, USA., Correa R; Department of Radiology, Mayo Clinic, 13400 East Shea Blvd, Scottsdale, AZ, 85259, USA., Boutin RD; Department of Radiology, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA., Maron DJ; Division of Cardiovascular Medicine, Department of Medicine, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA.; Department of Medicine, Stanford Prevention Research Center, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA., Rodriguez F; Division of Cardiovascular Medicine, Department of Medicine, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA., Sandhu AT; Division of Cardiovascular Medicine, Department of Medicine, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA., Rubin D; Department of Biomedical Data Science, Stanford University, 1265 Welch Road, MSOB West Wing, Third Floor, Stanford, CA, 94305, USA.; Department of Radiology, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA., Chaudhari AS; Department of Biomedical Data Science, Stanford University, 1265 Welch Road, MSOB West Wing, Third Floor, Stanford, CA, 94305, USA.; Department of Radiology, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA.; Cardiovascular Institute, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA., Patel BN; Department of Radiology, Mayo Clinic, 13400 East Shea Blvd, Scottsdale, AZ, 85259, USA. patel.bhavik@mayo.edu.

Publikováno v: Scientific reports [Sci Rep] 2023 Nov 29; Vol. 13 (1), pp. 21034. Date of Electronic Publication: 2023 Nov 29.