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Machine Learning Applications in Solid Organ Transplantation and Related Complications
2021
Frontiers in Immunology
The complexity of transplant medicine pushes the boundaries of innate, human reasoning. From networks of immune modulators to dynamic pharmacokinetics to variable postoperative graft survival to equitable allocation of scarce organs, machine learning promises to inform clinical decision making by deciphering prodigious amounts of available data. This paper reviews current research describing how algorithms have the potential to augment clinical practice in solid organ transplantation. We
doi:10.3389/fimmu.2021.739728
pmid:34603324
pmcid:PMC8481939
fatcat:wwuywxe4nncvzi7ftmluwk6ovm