ArticlePloS one2024
The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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Who cites it
20 citing papers in PubMed.
- Artificial Intelligence-Powered Histopathology in Stem Cell Research: Bridging Morphology, Function, and Omics.Current issues in molecular biology · 2026Review
- Revolutionizing Stem Cell Sorting with Machine Learning: A Review of Trends, Tools, and Future Directions.Iranian journal of medical sciences · 2026Review
- "Stem Cells in Regenerative Medicine: from Discovery and Molecular Mechanisms To Therapeutic Applications and Clinical Challenges".Cell biochemistry and biophysics · 2026Review
- Smarter stem cells: how AI is supercharging iPSC technology.Cell and tissue research · 2025Review
- Patient-derived induced pluripotent stem cells with a C9orf72 expansion as a model to study frontotemporal dementia pathologies.Molecular biology of the cell · 2025Article
- Applications of artificial intelligence in stem cell therapy.World journal of stem cells · 2025Review
- AI-Driven Quality Monitoring and Control in Stem Cell Cultures: A Comprehensive Review.Biotechnology journal · 2025Review
- Precision Recovery After Spinal Cord Injury: Integrating CRISPR Technologies, AI-Driven Therapeutics, Single-Cell Omics, and System Neuroregeneration.International journal of molecular sciences · 2025Review
- Multimodal AI in Biomedicine: Pioneering the Future of Biomaterials, Diagnostics, and Personalized Healthcare.Nanomaterials (Basel, Switzerland) · 2025Review
- Induced Pluripotent Stem Cells in Cardiomyopathy: Advancing Disease Modeling, Therapeutic Development, and Regenerative Therapy.International journal of molecular sciences · 2025Review
- AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing.Communications biology · 2025Article
- Decoding Aging through iPSC Reprogramming: Advances and Challenges.Aging and disease · 2025Review
- Emerging biotechnologies for engineering liver organoids.Bioactive materials · 2025Review
- Editorial: Paradigm shifts and innovations in cellular neuroscience.Frontiers in cellular neuroscience · 2025Article
- Advancements in theFrontiers in toxicology · 2025Review
- Oral stem cells in combination with hydrogels as biomimetic bioactive platforms for periodontal tissue engineering.Frontiers in oral health · 2025Review
- Artificial intelligence powers regenerative medicine into predictive realm.Regenerative medicine · 2024Review
- AI Revolutionizes Cellular Reprogramming of Periodontal Ligament.International dental journal · 2024Article
- Review
- Advances in physiological and clinical relevance of hiPSC-derived brain models for precision medicine pipelines.Frontiers in cellular neuroscience · 2024Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStem cell research, particularly in the domain of induced pluripotent stem cell (iPSC) technology, has shown significant progress. The integration of artificial intelligence (AI), especially machine learning (ML) and deep learning (DL), has played a pivotal role in refining iPSC classification, monitoring cell functionality, and conducting genetic analysis. These enhancements are broadening the applications of iPSC technology in disease modelling, drug screening, and regenerative medicine. This review aims to explore the role of AI in the advancement of iPSC research.
methodsIn December 2023, data were collected from three electronic databases (PubMed, Web of Science, and Science Direct) to investigate the application of AI technology in iPSC processing.
resultsThis systematic scoping review encompassed 79 studies that met the inclusion criteria. The number of research studies in this area has increased over time, with the United States emerging as a leading contributor in this field. AI technologies have been diversely applied in iPSC technology, encompassing the classification of cell types, assessment of disease-specific phenotypes in iPSC-derived cells, and the facilitation of drug screening using iPSC. The precision of AI methodologies has improved significantly in recent years, creating a foundation for future advancements in iPSC-based technologies.
conclusionsOur review offers insights into the role of AI in regenerative and personalized medicine, highlighting both challenges and opportunities. Although still in its early stages, AI technologies show significant promise in advancing our understanding of disease progression and development, paving the way for future clinical applications.
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