Application of Graph Neural Networks to surgical complication prediction

Most complex tumour resections are associated with severe complications. These complications cause delays in adjuvant therapy resulting in worsened treatment response or death. Machine learning-based prediction of postoperative patient outcomes, before the surgery, enables individualised treatment planning and improved postoperative patient management. In this talk, I will describe such a surgical complication prediction framework and present the challenges associated with its practical implementation. Additionally, with the help of a case study, I will demonstrate the use of Graph Neural Networks for complication prediction and the challenges thereof.