AIMC Topic: Tissue Donors

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Evaluation of Sociomedical Factors on Corneal Donor Recovery Using Machine Learning.

Ophthalmic epidemiology
PURPOSE: To evaluate co-morbid sociomedical conditions affecting corneal donor endothelial cell density and transplant suitability.

Artificial intelligence-driven automated lung sizing from chest radiographs.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Lung size measurements play an important role in transplantation, as optimal donor-recipient size matching is necessary to ensure the best possible outcome. Although several strategies for size matching are currently used, all have limitations, and n...

Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models.

Scientific reports
The decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses interpretabl...

Deceased-Donor Kidney Transplant Outcome Prediction Using Artificial Intelligence to Aid Decision-Making in Kidney Allocation.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
In kidney transplantation, pairing recipients with the highest longevity with low-risk allografts to optimize graft-donor survival is a complex challenge. Current risk prediction models exhibit limited discriminative and calibration capabilities and ...

Evaluating the performance of large language models in haematopoietic stem cell transplantation decision-making.

British journal of haematology
In a first-of-its-kind study, we assessed the capabilities of large language models (LLMs) in making complex decisions in haematopoietic stem cell transplantation. The evaluation was conducted not only for Generative Pre-trained Transformer 4 (GPT-4)...

A transformer-based deep learning approach for fairly predicting post-liver transplant risk factors.

Journal of biomedical informatics
Liver transplantation is a life-saving procedure for patients with end-stage liver disease. There are two main challenges in liver transplant: finding the best matching patient for a donor and ensuring transplant equity among different subpopulations...

A large-scale retrospective study enabled deep-learning based pathological assessment of frozen procurement kidney biopsies to predict graft loss and guide organ utilization.

Kidney international
Lesion scores on procurement donor biopsies are commonly used to guide organ utilization for deceased-donor kidneys. However, frozen sections present challenges for histological scoring, leading to inter- and intra-observer variability and inappropri...

Deep Learning-Based Survival Analysis for Receiving a Steatotic Donor Liver Versus Waiting for a Standard Liver.

Transplantation proceedings
BACKGROUND: An emerging strategy to expand the donor pool is the use of a steatotic donor liver (SDLs; ≥ 30% macrosteatosis on biopsy). With the obesity epidemic and prevalence of nonalcoholic fatty liver disease, SDLs have been reported in 59% of al...

Ethical concerns surrounding artificial intelligence in anatomy education: Should AI human body simulations replace donors in the dissection room?

Anatomical sciences education
The potential effects of artificial intelligence (AI) on the teaching of anatomy are unclear. We explore the hypothetical situation of human body donors being replaced by AI human body simulations and reflect on two separate ethical concerns: first, ...