Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Privacy-aware community infrastructureResearch graph
References from Machine Learning in Stem Cell Research: From Biological Data to Clinical Translation. Local targets link to admitted publications; unresolved targets remain external evidence.
A literature review: Machine learning-based stem cell investigation
10.21037/atm-23-1937 · 2024 · External reference
Exploring the current trends of artificial intelligence in stem cell therapy: A systematic review
2021 · External reference
Applications of artificial intelligence in stem cell therapy
10.4252/wjsc.v17.i8.106086 · 2025 · External reference
10.21037/sci-2020-001
10.21037/sci-2020-001 · External reference
10.1038/s41586-023-06139-9
10.1038/s41586-023-06139-9 · External reference
10.1038/s41592-024-02201-0
10.1038/s41592-024-02201-0 · External reference
10.1038/s41592-024-02305-7
10.1038/s41592-024-02305-7 · External reference
Pluripotent and multipotent stem cells and current therapeutic applications
2021 · External reference
Unresolved reference
External reference
Ten years of progress and promise of induced pluripotent stem cells: Historical origins, characteristics, mechanisms, limitations, and potential applications
10.7717/peerj.4370 · 2018 · External reference
Stem cells: Past, present, and future
10.1186/s13287-019-1165-5 · 2019 · External reference
10.1016/j.cell.2021.12.012
10.1016/j.cell.2021.12.012 · External reference
10.1016/j.stem.2013.12.005
10.1016/j.stem.2013.12.005 · External reference
10.3390/cells9102193
10.3390/cells9102193 · External reference
Unresolved reference
External reference
What is next generation sequencing?
10.1136/archdischild-2013-304340 · 2013 · External reference
Stem cell imaging: Tools to improve cell delivery and viability
10.1155/2016/9240652 · 2016 · External reference
Stem cell metabolic and spectroscopic profiling
10.1016/j.tibtech.2013.01.008 · 2013 · External reference
Concise review: Measuring physiological responses of human pluripotent stem cell derived cardiomyocytes to drugs and disease
10.1002/stem.2403 · 2016 · External reference
Unresolved reference
External reference
A survey on image data augmentation for deep learning
10.1186/s40537-019-0197-0 · 2019 · External reference
10.1007/978-1-0716-1839-4_7
10.1007/978-1-0716-1839-4_7 · External reference
10.1007/978-981-97-6703-8
10.1007/978-981-97-6703-8 · 2024 · External reference
Multimodal machine learning: A survey and taxonomy
10.1109/tpami.2018.2798607 · 2019 · External reference
Unresolved reference
External reference
10.1007/978-3-319-10590-1_53
10.1007/978-3-319-10590-1_53 · External reference
Semi-supervised learning in cancer diagnostics
10.3389/fonc.2022.960984 · 2022 · External reference
Unresolved reference
External reference
Regularization and variable selection via the elastic net
10.1111/j.1467-9868.2005.00503.x · 2005 · External reference
10.7551/mitpress/3206.001.0001
10.7551/mitpress/3206.001.0001 · External reference
10.1109/embc.2019.8856524
10.1109/embc.2019.8856524 · External reference
10.1109/jbhi.2024.3505955
10.1109/jbhi.2024.3505955 · External reference
10.1117/12.2549730
10.1117/12.2549730 · External reference
Machine learning-based classification of dual fluorescence signals reveals muscle stem cell fate transitions in response to regenerative niche factors
10.1038/s41536-023-00277-4 · 2023 · External reference
Lense: Optimizing data preprocessing in single-cell omics using large language models
10.1093/bib/bbag288 · 2026 · External reference
Multimodality representation learning: A survey on evolution, pretraining and its applications
10.1145/3617833 · 2024 · External reference
Assessing biomaterial-induced stem cell lineage fate by machine learning-based artificial intelligence
10.1002/adma.202210637 · 2023 · External reference
10.1093/dnares/dsr016
10.1093/dnares/dsr016 · External reference
Generative adversarial network model to classify human induced pluripotent stem cell-cardiomyocytes based on maturation level
10.1038/s41598-024-77943-0 · 2024 · External reference
Automated mesenchymal stem cell segmentation and machine learning-based phenotype classification using morphometric and textural analysis
2021 · External reference
10.1016/j.ymeth.2024.03.005
10.1016/j.ymeth.2024.03.005 · External reference
10.1021/acsbiomaterials.1c00418
10.1021/acsbiomaterials.1c00418 · External reference
Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine
10.1038/s41417-019-0105-y · 2020 · External reference
Deriving waveform parameters from calcium transients in human iPSC-derived cardiomyocytes to predict cardiac activity with machine learning
10.1016/j.stemcr.2022.01.009 · 2022 · External reference
10.1101/2023.11.24.568600
10.1101/2023.11.24.568600 · External reference
Predicting reprogramming-related gene expression from cell morphology in human induced pluripotent stem cells
10.1091/mbc.e22-06-0215 · 2023 · External reference
Data-driven maturity level evaluation for cardiomyocytes derived from human pluripotent stem cells (invited paper)
10.3390/electronics13244985 · 2024 · External reference
10.1093/stmcls/sxad039
10.1093/stmcls/sxad039 · External reference
10.3390/toxics12050354
10.3390/toxics12050354 · External reference
Machine learning to predict mesenchymal stem cell efficacy for cartilage repair
10.1371/journal.pcbi.1008275 · 2020 · External reference
Machine learning of stem cell identities from single-cell expression data via regulatory network archetypes
10.3389/fgene.2019.00002 · 2019 · External reference
10.1016/b978-0-443-15274-0.50433-9
10.1016/b978-0-443-15274-0.50433-9 · External reference
Machine learning based methodology to identify cell shape phenotypes associated with microenvironmental cues
10.1016/j.biomaterials.2016.06.040 · 2016 · External reference
Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status
10.1016/j.compbiomed.2020.104172 · 2021 · External reference
10.3390/biom10060931
10.3390/biom10060931 · External reference
10.1007/s13577-020-00446-3
10.1007/s13577-020-00446-3 · External reference
Gene expression classification using epigenetic features and DNA sequence composition in the human embryonic stem cell line H1
10.1016/j.gene.2016.07.059 · 2016 · External reference
SVM classifier to predict genes important for self-renewal and pluripotency of mouse embryonic stem cells
10.1186/1752-0509-4-173 · 2010 · External reference
Morphological signal processing for phenotype recognition of human pluripotent stem cells using machine learning methods
2023 · External reference
A novel machine learning based approach for iPS progenitor cell identification
10.1371/journal.pcbi.1007351 · 2019 · External reference
A machine learning assisted, label-free, non-invasive approach for somatic reprogramming in induced pluripotent stem cell colony formation detection and prediction
10.1038/s41598-017-13680-x · 2017 · External reference
Human embryonic stem cell classification: Random network with autoencoded feature extractor
2021 · External reference
Prediction of stem cell state using cell image-based deep learning
10.1002/aisy.202300017 · 2023 · External reference
A comprehensive analysis of gene expression changes in a high replicate and open-source dataset of differentiating hiPSC-derived cardiomyocytes
10.1038/s41598-021-94732-1 · 2021 · External reference
10.1109/cdc.2018.8619300
10.1109/cdc.2018.8619300 · External reference
Machine learning predicts putative hematopoietic stem cells within large single-cell transcriptomics data sets
10.1016/j.exphem.2019.08.009 · 2019 · External reference
10.1101/2025.09.02.673063
10.1101/2025.09.02.673063 · External reference
10.1016/j.cels.2017.08.009
10.1016/j.cels.2017.08.009 · External reference
Identification of gene expression signatures across different types of neural stem cells with the Monte-Carlo feature selection method
10.1002/jcb.26507 · 2018 · External reference
10.1182/blood.2020006229
10.1182/blood.2020006229 · External reference
10.1016/j.cels.2020.11.004
10.1016/j.cels.2020.11.004 · External reference
Deep learning neural networks highly predict very early onset of pluripotent stem cell differentiation
10.1016/j.stemcr.2019.02.004 · 2019 · External reference
10.1093/stmcls/sxad049
10.1093/stmcls/sxad049 · External reference
Predicting multipotency of human adult stem cells derived from various donors through deep learning
10.1038/s41598-022-25423-8 · 2022 · External reference
Recognizing the differentiation degree of human induced pluripotent stem cell-derived retinal pigment epithelium cells using machine learning and deep learning-based approaches
10.3390/cells12020211 · 2023 · External reference
Deep learning-based predictive identification of neural stem cell differentiation
10.1038/s41467-021-22758-0 · 2021 · External reference
Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors
10.1186/s13287-024-03682-8 · 2024 · External reference
Morphology-based deep learning approach for predicting adipogenic and osteogenic differentiation of human mesenchymal stem cells (hMSCs)
10.3389/fcell.2023.1329840 · 2023 · External reference
Deep learning predicts the differentiation of kidney organoids derived from human induced pluripotent stem cells
10.23876/j.krcp.22.017 · 2023 · External reference
Machine learning and metabolomics predict mesenchymal stem cell osteogenic differentiation in 2D and 3D cultures
10.3390/jfb15120367 · 2024 · External reference
10.1016/j.jcyt.2019.12.006
10.1016/j.jcyt.2019.12.006 · External reference
Analysis of mesenchymal stem cell differentiation in vitro using classification association rule mining
10.1142/s0219720009004424 · 2009 · External reference
Machine learning for stem cell differentiation and proliferation classification on electrical impedance spectroscopy
10.2478/joeb-2019-0018 · 2019 · External reference
Prediction of human induced pluripotent stem cell cardiac differentiation outcome by multifactorial process modeling
10.3389/fbioe.2020.00851 · 2020 · External reference
Aging induces aberrant state transition kinetics in murine muscle stem cells
10.1242/dev.183855 · 2020 · External reference
10.1007/978-981-16-0425-6_26
10.1007/978-981-16-0425-6_26 · External reference
Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data
10.1038/s41598-024-58010-0 · 2024 · External reference
10.1007/978-3-030-00928-1_66
10.1007/978-3-030-00928-1_66 · External reference
10.1073/pnas.2001906117
10.1073/pnas.2001906117 · External reference
Re assessment of marker genes in human induced pluripotent stem cells for enhanced quality control
10.1038/s41467-024-52922-1 · 2024 · External reference
Machine learning-based quality control of contractility of cultured human induced pluripotent stem-cell-derived cardiomyocytes
10.1016/j.bbrc.2020.03.141 · 2020 · External reference
A live-cell image-based machine learning strategy for reducing variability in PSC differentiation systems
10.1038/s41421-023-00543-1 · 2023 · External reference
High throughput screening of mesenchymal stem cell lines using deep learning
10.1038/s41598-022-21653-y · 2022 · External reference
Deep learning-based quality control of cultured human-induced pluripotent stem cell-derived cardiomyocytes
10.1016/j.jphs.2019.04.008 · 2019 · External reference
Machine learning approach to automated quality identification of human induced pluripotent stem cell colony images
10.1155/2016/3091039 · 2016 · External reference
10.1016/j.stemcr.2021.03.018
10.1016/j.stemcr.2021.03.018 · External reference
Automated gating of CD34+ cells in cord blood: Performance evaluation of a machine learning based ISHAGE protocol
10.1002/cyto.a.70017 · 2026 · External reference
10.1016/j.cell.2015.11.007
10.1016/j.cell.2015.11.007 · External reference
10.2174/1574888x18666230714151746
10.2174/1574888x18666230714151746 · External reference
Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy
10.3389/fimmu.2024.1464698 · 2024 · External reference
Identification of the hub genes involved in stem cell treatment for intervertebral disc degeneration: A conjoint analysis of single-cell and machine learning
10.1155/2023/7055264 · 2023 · External reference
Integrative analysis of gene expression and DNA methylation through one-class logistic regression machine learning identifies stemness features in medulloblastoma
10.1002/1878-0261.12557 · 2019 · External reference
10.1002/ana.26047
10.1002/ana.26047 · External reference
10.1016/j.imu.2019.01.006
10.1016/j.imu.2019.01.006 · External reference
Detection of genetic cardiac diseases by Ca2+ transient profiles using machine learning methods
10.1038/s41598-018-27695-5 · 2018 · External reference
Machine learning identifies abnormal Ca2+ transients in human induced pluripotent stem cell-derived cardiomyocytes
10.1038/s41598-020-73801-x · 2020 · External reference
AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data
10.1093/bib/bbae207 · 2024 · External reference
10.1016/j.ymthe.2021.06.017
10.1016/j.ymthe.2021.06.017 · External reference
Machine learning of human pluripotent stem cell-derived engineered cardiac tissue contractility for automated drug classification
10.1016/j.stemcr.2017.09.008 · 2017 · External reference
Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes and machine learning
10.1016/j.taap.2022.116342 · 2023 · External reference
Deep learning detects cardiotoxicity in a high-content screen with induced pluripotent stem cell-derived cardiomyocytes
10.7554/elife.68714 · 2021 · External reference
3D in vivo magnetic particle imaging of human stem cell-derived islet organoid transplantation using a machine learning algorithm
10.3389/fcell.2021.704483 · 2021 · External reference
Supervised machine learning for classification of the electrophysiological effects of chronotropic drugs on human induced pluripotent stem cell derived cardiomyocytes
10.1371/journal.pone.0144572 · 2015 · External reference
Analysis of drug effects on iPSC cardiomyocytes with machine learning
10.1007/s10439-020-02521-0 · 2021 · External reference
Prediction of drug induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
10.1038/srep12337 · 2015 · External reference
Comparing the efficacy and safety of cell transplantation for spinal cord injury: A systematic review and Bayesian network meta-analysis
10.3389/fncel.2022.860131 · 2022 · External reference
Machine learning reveals the rules governing the efficacy of mesenchymal stromal cells in septic preclinical models
10.1186/s13287-024-03873-3 · 2024 · External reference
A Bayesian network analysis of the efficacy of scaffolds and stem cells in spinal cord injury treatment
10.2174/1574888x18666221025155807 · 2023 · External reference
Mesenchymal stem cells: A new choice for nonsurgical treatment of OA? Results from a Bayesian network meta-analysis
10.1155/2021/6663003 · 2021 · External reference
Transplantation induces profound changes in the transcriptional asset of hematopoietic stem cells: Identification of specific signatures using machine learning techniques
10.3390/jcm9061670 · 2020 · External reference
Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19
10.1186/s13287-023-03573-4 · 2023 · External reference
Predicting the availability of hematopoietic stem cell donors using machine learning
10.1016/j.bbmt.2020.03.026 · 2020 · External reference
Machine learning–based scoring models to predict hematopoietic stem cell mobilization in allogeneic donors
10.1182/bloodadvances.2021005149 · 2022 · External reference
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
10.1200/jco.2014.59.1339 · 2015 · External reference
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
10.1002/cam4.2401 · 2019 · External reference
Bayesian networks: A new approach to predict therapeutic range achievement of initial cyclosporine blood concentration after pediatric hematopoietic stem cell transplantation
10.1007/s40268-017-0223-7 · 2018 · External reference
A machine learning and explainable artificial intelligence approach for predicting the efficacy of hematopoietic stem cell transplant in pediatric patients
10.1016/j.health.2023.100170 · 2023 · External reference
Survival prediction in allogeneic haematopoietic stem cell transplant recipients using pre and post-transplant factors and computational intelligence
10.1111/jcmm.70672 · 2025 · External reference
Clinical and genetic risk prediction of cognitive impairment after blood or marrow transplantation for hematologic malignancy
10.1200/jco.19.01085 · 2020 · External reference
A deep learning algorithm to translate and classify cardiac electrophysiology
10.7554/elife.68335 · 2021 · External reference
