AIMC Topic: Hematopoietic Stem Cell Transplantation

Clear Filters Showing 1 to 10 of 50 articles

Development and prospective evaluation of a machine learning model to predict vomiting among pediatric cancer and hematopoietic cell transplant patients.

BMC cancer
PURPOSE: Objectives were to develop a machine learning (ML) model based on electronic health record (EHR) data to predict the risk of vomiting within a 96-hour window after admission to the pediatric oncology and hematopoietic cell transplant (HCT) s...

Autonomous artificial intelligence prescribing a drug to prevent severe acute graft-versus-host disease in HLA-haploidentical transplants.

Nature communications
Autonomous artificial intelligence (AI) models for deciding treatment strategies are available but rarely applied prospectively in clinical settings. Here we present a prospective study of deploying daGOAT, an algorithm we have developed, as a condit...

Enteral versus parenteral nutrition in auto-HCT: a randomized controlled trial on clinical outcomes and gut microbiome dynamics.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Disruption of the gut microbiome is a common consequence of chemotherapy, linked with detrimental treatment outcomes (e.g. sepsis), especially in haematopoietic stem cell transplant (HCT) recipients. Preclinical data suggest that enteral nutrition (E...

Microbiome-based prediction of allogeneic hematopoietic stem cell transplantation outcome.

Genome medicine
BACKGROUND: Allogeneic hematopoietic stem cell transplantation (HSCT) is potentially curative for hematologic malignancies but is frequently complicated by relapse and immune-mediated complications, such as graft-versus-host disease (GVHD). Emerging ...

Febrile neutropenia management in high-risk neutropenic patients: a narrative review on antibiotic prophylaxis and empirical treatment.

Expert review of anti-infective therapy
INTRODUCTION: Although febrile neutropenia (FN) remains a major cause of morbidity and mortality in patients with hematologic malignancies and hematopoietic stem cell transplant (HSCT) recipients, the increasing prevalence of antimicrobial resistance...

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...

Raising awareness may increase the likelihood of hematopoietic stem cell donation: a nationwide survey using artificial intelligence.

International journal of hematology
BACKGROUND: In Italy, the demand for allogeneic transplantation exceeds the number of compatible donors in the Italian Bone Marrow Donor Registry (IBMDR). This study aimed to explore the knowledge, beliefs, opinions, values, and feelings of the Itali...

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...

A machine learning-based workflow for predicting transplant outcomes in patients with sickle cell disease.

British journal of haematology
Allogeneic haematopoietic cell transplantation (HCT) with HLA-matched sibling donor remains the most established curative therapeutic option for patients with sickle cell disease (SCD). However, it is not without risks, highlighting the need for a ri...