AIMC Topic: Hematopoietic Stem Cell Transplantation

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Artificial Intelligence Approaches in Hematopoietic Cell Transplantation: A Review of the Current Status and Future Directions.

Turkish journal of haematology : official journal of Turkish Society of Haematology
The evidence-based literature on healthcare is currently expanding exponentially. The opportunities provided by the advancement in artificial intelligence (AI) tools such as machine learning are appealing in tackling many of the current healthcare ch...

A cure-rate model for Q-learning: Estimating an adaptive immunosuppressant treatment strategy for allogeneic hematopoietic cell transplant patients.

Biometrical journal. Biometrische Zeitschrift
Cancers treated by transplantation are often curative, but immunosuppressive drugs are required to prevent and (if needed) to treat graft-versus-host disease. Estimation of an optimal adaptive treatment strategy when treatment at either one of two st...

Evaluation of a Machine Learning-Based Prognostic Model for Unrelated Hematopoietic Cell Transplantation Donor Selection.

Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation
The survival of patients undergoing hematopoietic cell transplantation (HCT) from unrelated donors for acute leukemia exhibits considerable variation, even after stringent genetic matching. To improve the donor selection process, we attempted to crea...

Novel composite health assessment risk model for older allogeneic transplant recipients: BMT-CTN 1704.

Blood advances
Allogeneic hematopoietic cell transplantation (allo-HCT) is potentially curative for older adults with hematologic malignancies. Concerns on nonrelapse mortality (NRM) in older adults limit allo-HCT utilization. We executed a prospective, observation...

Use of machine learning techniques to predict poor survival after hematopoietic cell transplantation for myelofibrosis.

Blood
With the incorporation of effective therapies for myelofibrosis (MF), accurately predicting outcomes after allogeneic hematopoietic cell transplantation (allo-HCT) is crucial for determining the optimal timing for this procedure. Using data from 5183...

Establishment of a machine learning-based prediction framework to assess trade-offs in decisions that affect post-HCT outcomes.

Computers in biology and medicine
In this study, we propose a conceptual framework of decision support tools, built upon machine learning and multi-objective optimization, aimed at offering a deeper understanding of the complex trade-offs involved in hematopoietic stem cell transplan...

Application of artificial intelligence and machine learning for risk stratification acute kidney injury among hematopoietic stem cell transplantation patients: PCRRT ICONIC AI Initiative Group Meeting Proceedings.

Clinical nephrology
Acute kidney injury (AKI) is a frequent, severe complication of hematopoietic stem cell transplantation (HSCT) and is associated with an increased risk of morbidity and mortality. Recent advances in artificial intelligence (AI) and machine learning (...

Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD).

Frontiers in immunology
BACKGROUND: Acute intestinal graft-versus-host disease (AIGVHD) is a common complication of allogeneic hematopoietic stem cell transplantation (allo HSCT) with a high mortality rate. The primary aim of the present study is to identify tissue-based ge...