AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Transplantation, Homologous

Showing 11 to 20 of 20 articles

Clear Filters

Renal Function Impairment in Kidney Transplantation: Importance of Early BK Virus Detection.

Transplantation proceedings
BACKGROUND: BK virus allograft nephropathy is a major complication of kidney transplantation that markedly reduces graft survival (50% graft failure 24 months after being diagnosed). BK virus replication can occur at any time posttransplantation. Vir...

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...

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 ...

Using a machine learning algorithm to predict acute graft-versus-host disease following allogeneic transplantation.

Blood advances
Acute graft-versus-host disease (aGVHD) is 1 of the critical complications that often occurs following allogeneic hematopoietic stem cell transplantation (HSCT). Thus far, various types of prediction scores have been created using statistical calcula...

A BLSTM with Attention Network for Predicting Acute Myeloid Leukemia Patient's Prognosis using Comprehensive Clinical Parameters.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The prognosis management is crucial for highrisk disease like Acute Myeloid Leukemia (AML) in order to support decisions of clinical treatment. However, the challenges of accurate and consistent forecasting lie in the high variability of the disease ...

Machine learning reveals chronic graft--host disease phenotypes and stratifies survival after stem cell transplant for hematologic malignancies.

Haematologica
The application of machine learning in medicine has been productive in multiple fields, but has not previously been applied to analyze the complexity of organ involvement by chronic graft--host disease. Chronic graft--host disease is classified by an...