ArticleScientific reports2024
Development and validation of a cuproptosis-related prognostic model for acute myeloid leukemia patients using machine learning with stacking.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Artificial intelligence-based prognostic models in acute myeloid leukemia: systematic review and meta-analysis.Blood neoplasia · 2026Article
- Multi-omics driven computational framework for cancer molecular subtype classification.Scientific reports · 2025Article
- Development and validation of a machine learning model for predicting venous thromboembolism complications following colorectal cancer surgery.Visual computing for industry, biomedicine, and art · 2025Article
- Unveiling the role of coagulation-related genes in acute myeloid leukemia prognosis and immune microenvironment through machine learning.European journal of medical research · 2025Article
- Age-stratified machine learning identifies divergent prognostic significance of molecular alterations in AML.HemaSphere · 2025Article
- Cuproptosis: A Review on Mechanisms, Role in Solid and Hematological Tumors, and Association with Viral Infections.Mediterranean journal of hematology and infectious diseases · 2025Review
- A novel deep learning based approach with hyperparameter selection using grey wolf optimization for leukemia classification and hematologic malignancy detection.PeerJ. Computer science · 2025Article
- MT1E in AML: a gateway to understanding regulatory cell death and immunotherapeutic responses.Journal of leukocyte biology · 2024Article
- Exploring and clinical validation of prognostic significance and therapeutic implications of copper homeostasis-related gene dysregulation in acute myeloid leukemia.Annals of hematology · 2024Article
- Stem cell status and prognostic applications of cuproptosis-associated lncRNAs in acute myeloid leukemia.Frontiers in cell and developmental biology · 2024Article
- Ferroptosis-Related Gene Signature for Prognosis Prediction in Acute Myeloid Leukemia and Potential Therapeutic Options.International journal of general medicine · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
Our objective is to develop a prognostic model focused on cuproptosis, aimed at predicting overall survival (OS) outcomes among Acute myeloid leukemia (AML) patients. The model utilized machine learning algorithms incorporating stacking. The GSE37642 dataset was used as the training data, and the GSE12417 and TCGA-LAML cohorts were used as the validation data. Stacking was used to merge the three prediction models, subsequently using a random survival forests algorithm to refit the final model using the stacking linear predictor and clinical factors. The prediction model, featuring stacking linear predictor and clinical factors, achieved AUC values of 0.840, 0.876 and 0.892 at 1, 2 and 3 years within the GSE37642 dataset. In external validation dataset, the corresponding AUCs were 0.741, 0.754 and 0.783. The predictive performance of the model in the external dataset surpasses that of the model simply incorporates all predictors. Additionally, the final model exhibited good calibration accuracy. In conclusion, our findings indicate that the novel prediction model refines the prognostic prediction for AML patients, while the stacking strategy displays potential for model integration.
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