Public articles linked to the same research event.
World journal of transplantation This review summarizes applications of artificial intelligence and machine learning across the transplantation surgery care pathway, covering preoperative anatomical assessment, graft weight estimation and candidate selection, perioperative prediction of massive transfusion, hemorrhage and acute kidney injury plus robotic-assisted surgery, postoperative early prediction of sepsis, pneumonia and graft dysfunction with long-term monitoring, and cross-cutting innovations such as hyperspectral imaging and automated histopathological evaluation, while noting that multimodal models integrating electronic health records, intraoperative signals, ultrasound and histology can bridge diagnostic, prognostic and therapeutic decision-making, though clinical translation still requires rigorous validation
This review summarizes applications of artificial intelligence and machine learning across the transplantation surgery care pathway, covering preoperative anatomical assessment, graft weight estimation and candidate selection, perioperative prediction of massive transfusion, hemorrhage and acute kidney injury plus robotic-assisted surgery, postoperative early prediction of sepsis, pneumonia and graft dysfunction with long-term monitoring, and cross-cutting innovations such as hyperspectral imaging and automated histopathological evaluation, while noting that multimodal models integrating electronic health records, intraoperative signals, ultrasound and histology can bridge diagnostic, prognostic and therapeutic decision-making, though clinical translation still requires rigorous validation
This review summarizes applications of artificial intelligence and machine learning across the transplantation surgery care pathway, covering preoperative anatomical assessment, graft weight estimation and candidate selection, perioperative prediction of massive transfusion, hemorrhage and acute kidney injury plus robotic-assisted surgery, postoperative early prediction of sepsis, pneumonia and graft dysfunction with long-term monitoring, and cross-cutting innovations such as hyperspectral imaging and automated histopathological evaluation, while noting that multimodal models integrating electronic health records, intraoperative signals, ultrasound and histology can bridge diagnostic, prognostic and therapeutic decision-making, though clinical translation still requires rigorous validation
This review summarizes applications of artificial intelligence and machine learning across the transplantation surgery care pathway, covering preoperative anatomical assessment, graft weight estimation and candidate selection, perioperative prediction of massive transfusion, hemorrhage and acute kidney injury plus robotic-assisted surgery, postoperative early prediction of sepsis, pneumonia and graft dysfunction with long-term monitoring, and cross-cutting innovations such as hyperspectral imaging and automated histopathological evaluation, while noting that multimodal models integrating electronic health records, intraoperative signals, ultrasound and histology can bridge diagnostic, prognostic and therapeutic decision-making, though clinical translation still requires rigorous validation