AIMC Topic: Hematopoietic Stem Cell Transplantation

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A Systematic Review of Machine Learning Techniques in Hematopoietic Stem Cell Transplantation (HSCT).

Sensors (Basel, Switzerland) Oct 27, 2020
Machine learning techniques are widely used nowadays in the healthcare domain for the diagnosis, prognosis, and treatment of diseases. These techniques have applications in the field of hematopoietic cell transplantation (HCT), which is a potentially...
Machine Learning Bayes Theorem Graft vs Host Disease Hematopoietic Stem Cell Transplantation Humans
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Machine learning predicts stem cell transplant response in severe scleroderma.

Annals of the rheumatic diseases Sep 15, 2020
OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT...
Gene Expression Profiling Transcriptome Treatment Outcome Immunosuppressive Agents Adult Hematopoietic Stem Cell Transplantation Male Cyclophosphamide Middle Aged Scleroderma, Diffuse Humans Machine Learning Female
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Machine Learning Classification Algorithms to Predict aGvHD following Allo-HSCT: A Systematic Review.

Methods of information in medicine Apr 29, 2020
BACKGROUND:  The acute graft-versus-host disease (aGvHD) is the most important cause of mortality in patients receiving allogeneic hematopoietic stem cell transplantation. Given that it occurs at the stage of severe tissue damage, its diagnosis is la...
Graft vs Host Disease Humans Information Storage and Retrieval Machine Learning Hematopoietic Stem Cell Transplantation Algorithms Transplantation, Homologous
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Patient-based prediction algorithm of relapse after allo-HSCT for acute Leukemia and its usefulness in the decision-making process using a machine learning approach.

Cancer medicine Jul 15, 2019
Although allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for high-risk acute leukemia (AL), some patients still relapse. Since patients simultaneously have many prognostic factors, difficulties are associated with...
Prognosis Clinical Decision-Making Female Young Adult Humans Machine Learning Algorithms Middle Aged Patient Participation Adult Models, Theoretical Survival Analysis Leukemia, Myeloid, Acute Treatment Outcome Disease Management Male Decision Trees Hematopoietic Stem Cell Transplantation Transplantation, Homologous
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Machine learning reveals chronic graft--host disease phenotypes and stratifies survival after stem cell transplant for hematologic malignancies.

Haematologica Sep 20, 2018
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...
Chronic Disease Graft vs Host Disease Hematopoietic Stem Cell Transplantation Transplantation, Homologous Middle Aged Consensus United States National Institutes of Health (U.S.) Machine Learning Prospective Studies Biomarkers Female Adult Hematologic Neoplasms Male Humans
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Registries and artificial intelligence: investing in the future of hematopoietic cell transplantation.

Bone marrow transplantation Aug 31, 2018
Registries Hematopoietic Stem Cell Transplantation Humans Transplantation Conditioning Artificial Intelligence
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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 Jun 8, 2018
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...
Transplantation Conditioning Humans Artificial Intelligence Hematopoietic Stem Cell Transplantation
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A cure-rate model for Q-learning: Estimating an adaptive immunosuppressant treatment strategy for allogeneic hematopoietic cell transplant patients.

Biometrical journal. Biometrische Zeitschrift May 16, 2018
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...
Treatment Outcome Immunosuppressive Agents Graft vs Host Disease Hematopoietic Stem Cell Transplantation Humans Biostatistics Machine Learning Neoplasms
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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 Feb 2, 2018
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...
Humans Machine Learning Algorithms Prognosis Survival Rate Predictive Value of Tests Unrelated Donors Acute Disease Hematopoietic Stem Cell Transplantation Donor Selection Leukemia
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Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology Aug 3, 2015
PURPOSE: Allogeneic hematopoietic stem-cell transplantation (HSCT) is potentially curative for acute leukemia (AL), but carries considerable risk. Machine learning algorithms, which are part of the data mining (DM) approach, may serve for transplanta...
Kaplan-Meier Estimate Data Mining Hematopoietic Stem Cell Transplantation Transplantation, Homologous Precursor Cell Lymphoblastic Leukemia-Lymphoma Area Under Curve Male Registries Middle Aged Disease-Free Survival Risk Assessment Postoperative Complications Humans Risk Factors Decision Support Techniques Machine Learning Adult Retrospective Studies Treatment Outcome Disease Progression Algorithms Leukemia, Myeloid, Acute Female Europe Time Factors Reproducibility of Results Decision Trees ROC Curve Predictive Value of Tests Logistic Models
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