In addition, the increasing medical complexity of transplant candidates with their advanced age, metabolic risk factors, and cardiovascular comorbidities is associated with higher risks of morbidity and mortality on the waiting list and after transplant, resulting in higher risk of infections, malignancy, and medication-induced side effects. Organ allocation is a major limiting factor as there is constant increased demand while the donor organ supply is limited 1. Nonetheless, there remain challenges at various levels of the transplant journey. There has been tremendous progress in the outcomes of solid-organ transplantation in recent decades. Future work is required to improve the interpretability of these algorithms, ensure generalizability through larger-scale external validation, and establishment of infrastructure to permit clinical integration. In summary, these studies showed that ML techniques hold great potential to improve the outcome of transplant recipients. 36 articles were selected after a comprehensive search of the following databases: Ovid MEDLINE Ovid MEDLINE Epub Ahead of Print and In-Process & Other Non-Indexed Citations Ovid Embase Cochrane Database of Systematic Reviews (Ovid) and Cochrane Central Register of Controlled Trials (Ovid). In this review, we provide insight into the various applications of ML in transplant medicine, why these were used to evaluate a specific clinical question, and the potential of ML to transform the care of transplant recipients. ML algorithms have been applied in predictive modeling of waitlist mortality, donor–recipient matching, survival prediction, post-transplant complications diagnosis, and prediction, aiming to optimize immunosuppression and management. The growing abundance of clinical, genetic, radiologic, and metabolic data in transplantation has led to increasing interest in applying machine-learning (ML) tools that can uncover hidden patterns in large datasets. Improvements in long-term graft and patient survival require data-driven diagnosis and management of post-transplant complications. The growing disparity between organ demand and supply requires optimal patient/donor selection and matching. Alongside the tremendous progress in the last several decades, new challenges have emerged. Solid-organ transplantation is a life-saving treatment for end-stage organ disease in highly selected patients.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |