AI Medical Compendium Topic

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Transplantation, Homologous

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Artificial intelligence methods to estimate overall mortality and non-relapse mortality following allogeneic HCT in the modern era: an EBMT-TCWP study.

Bone marrow transplantation
Allogeneic haematopoietic cell transplantation (alloHCT) has curative potential counterbalanced by its toxicity. Prognostic scores fail to include current era patients and alternative donors. We examined adult patients from the EBMT registry who unde...

The 2022 Banff Meeting Lung Report.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
The Lung Session of the 2022 16th Banff Foundation for Allograft Pathology Conference-held in Banff, Alberta-focused on non-rejection lung allograft pathology and novel technologies for the detection of allograft injury. A multidisciplinary panel rev...

An artificial intelligence-driven predictive model for pediatric allogeneic hematopoietic stem cell transplantation using clinical variables.

European journal of haematology
BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is a procedure with high morbidity and mortality. Identifying patients for maximum benefit and risk assessment is crucial in the decision-making process. This has led to the development of pr...

Transplant nephropathology: Wherefrom, wherein, and whereto.

Clinical transplantation
Renal pathology is a relatively recent entry in nephrology. While diseases of the kidney are old, their study began in the 19th century with the report of Richard Bright of the lesions of end-stage kidney disease. Its easy diagnosis from albuminuria ...

Leveraging machine learning for predicting acute graft-versus-host disease grades in allogeneic hematopoietic cell transplantation for T-cell prolymphocytic leukaemia.

BMC medical research methodology
Orphan diseases, exemplified by T-cell prolymphocytic leukemia, present inherent challenges due to limited data availability and complexities in effective care. This study delves into harnessing the potential of machine learning to enhance care strat...

Differential impact of CD34+ cell dose for different age groups in allogeneic hematopoietic cell transplantation for acute leukemia: a machine learning-based discovery.

Experimental hematology
Allogeneic hematopoietic cell transplantation (allo-HCT) presents a potentially curative treatment for hematologic malignancies yet carries associated risks and complications. Continuous research focuses on predicting outcomes and identifying risk fa...

Novel machine learning technique further clarifies unrelated donor selection to optimize transplantation outcomes.

Blood advances
We investigated the impact of donor characteristics on outcomes in allogeneic hematopoietic cell transplantation (HCT) recipients using a novel machine learning approach, the Nonparametric Failure Time Bayesian Additive Regression Trees (NFT BART). N...

Pre-transplant and transplant parameters predict long-term survival after hematopoietic cell transplantation using machine learning.

Transplant immunology
BACKGROUND: Allogeneic hematopoietic stem transplantation (allo-HSCT) constitutes a curative treatment for various hematological malignancies. However, various complications limit the therapeutic efficacy of this approach, increasing the morbidity an...