AIMC Topic: Graft Survival

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Identify Hard-to-Place Kidneys for Early Engagement in Accelerated Placement With a Deep Learning Optimization Approach.

Transplantation proceedings
Recommended practices that follow match-run sequences for hard-to-place kidneys succumb to many declines, accruing cold ischemic time and exacerbating kidney quality that may lead to unnecessary kidney discard. Hard-to-place deceased donor kidneys ac...

Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies.

Kidney international
Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft failure. Here we sought an objective, quantitative pathological assessment of these lesions to improve predictive utility and constructed a deep-learn...

Machine Learning Applications in Solid Organ Transplantation and Related Complications.

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...

Patterns of 1,748 Unique Human Alloimmune Responses Seen by Simple Machine Learning Algorithms.

Frontiers in immunology
Allele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft acceptance before and after organ transplantation and therefore routinely studied during the patien...

Development and Evaluation of a Machine Learning Prediction Model for Flap Failure in Microvascular Breast Reconstruction.

Annals of surgical oncology
BACKGROUND: Despite high success rates, flap failure remains an inherent risk in microvascular breast reconstruction. Identifying patients who are at high risk for flap failure would enable us to recommend alternative reconstructive techniques. Howev...

Autologous fat graft assisted by stromal vascular fraction improves facial skin quality: A randomized controlled trial.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Cell-assisted lipotransfer (CAL) promotes the survival of fat grafts with high vascular density and improves skin quality by increasing collagen content. However, no study has quantified the changes on the skin surface, and rigorous metho...

Using machine learning techniques to develop risk prediction models to predict graft failure following kidney transplantation: protocol for a retrospective cohort study.

F1000Research
A mechanism to predict graft failure before the actual kidney transplantation occurs is crucial to clinical management of chronic kidney disease patients.  Several kidney graft outcome prediction models, developed using machine learning methods, are...

[Renal graft survival in patients transplanted from organs of deceased donors].

Revista medica del Instituto Mexicano del Seguro Social
BACKGROUND: In Mexico, out of the total number of transplants it was reported, in 2014, a frequency of 29% of deceased donor renal transplantation (DDRT). The use of kidneys from deceased elderly donors is increasing over the years. Currently, some a...