There has been significant interest in using machine learning algorithms to predict kidney transplant outcomes, such as the number of years until a graft inevitably fails. These prediction algorithms could possibly be used for pre-transplant donor-recipient matching to identify more compatible donors and recipients and thus improve post-transplant outcomes.
arXiv:2608. 03017v1 Announce Type: new Abstract: There has been significant interest in using machine learning algorithms to predict kidney transplant outcomes, such as the number of years until a graft inevitably fails.
arXiv:2507. 07339v2 Announce Type: replace-cross Abstract: Decisions about managing patients on the heart transplant waitlist are currently made by committees of doctors who consider multiple factors, but the process remains largely ad-hoc.
arXiv:2606. 02671v1 Announce Type: cross Abstract: Machine learning predictors have become essential tools for guiding automated decision making.
arXiv:2607. 15380v1 Announce Type: cross Abstract: Electronic health records combine free-text clinical narratives with structured measurements such as vital signs, laboratory values, and comorbidities.
arXiv:2608. 00271v1 Announce Type: cross Abstract: A wide range of statistical and machine learning methods have been proposed for survival analysis with competing risks, where the occurrence of one event (i.
arXiv:2606. 12006v1 Announce Type: cross Abstract: Predicting time-to-event outcomes such as mortality is a fundamental task in clinical decision-making, commonly addressed through survival analysis.
arXiv:2606. 14608v1 Announce Type: cross Abstract: Survival prediction plays a central role for healthcare providers and clinical researchers.
arXiv:2607. 16802v1 Announce Type: new Abstract: Deep survival models are evaluated almost exclusively by the concordance index (C-index), yet they are commonly trained using likelihood objectives such as the Cox partial likelihood, discrete-time negative log-likelihood, and DeepHit likelihood.
arXiv:2511. 02340v3 Announce Type: replace Abstract: Chronic Kidney Disease (CKD) affects nearly 10\% of the global population and often progresses to end-stage renal failure.
arXiv:2607. 29090v1 Announce Type: new Abstract: Postoperative adverse events, including mortality and morbidity, remain a major global burden, many of which are preventable through early identification of high-risk patients and targeted perioperative care.
arXiv:2607. 09165v1 Announce Type: cross Abstract: Achieving early and timely diagnosis and treatment for disease is a major challenge.
arXiv:2608. 17174v1 Announce Type: new Abstract: Chronic kidney disease (CKD) progresses silently and severely undermines quality of life, making early detection critical for improving patient outcomes.