Towards the Digital Lung: A Deep Learning Approach to Simulating Physiological Lung Function During Ex Vivo Lung Perfusion
Purpose: Ex vivo lung perfusion (EVLP) is an established reconditioning platform that generates multi-modal physiological data from isolated human lungs and is, thus, well-suited for machine learning. Digital twins —computer simulations of physical objects—are an emerging concept in medicine; however, they are unexplored in transplant medicine. Herein, we describe the development of a deep learning approach to simulate physiological lung function by leveraging high-resolution time-series lung ventilation d ata and demonstrate its predictive utility during EVLP.
Source: The Journal of Heart and Lung Transplantation - Category: Transplant Surgery Authors: , L. Del Sorbo, O. Hough, T. Borrillo, M. Grubert Van Iderstine, B.T. Chao, L. Orsini, J. Valero, M. Cypel, B. Wang, S. Keshavjee, A.T. Sage Source Type: research
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