ArticleACS biomaterials science & engineering2021
Machine Learning Techniques to Classify Healthy and Diseased Cardiomyocytes by Contractility Profile.
Article in ACS biomaterials science & engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 26 citations in OpenAlex.
- A Generative AI Framework to Predict Cardiomyocyte Contraction Function from Single Static Images.Advanced intelligent discovery · 2026Article
- Artificial Intelligence-Powered Histopathology in Stem Cell Research: Bridging Morphology, Function, and Omics.Current issues in molecular biology · 2026Review
- A Generative AI Framework to Predict Cardiomyocyte Contraction Function from Single Static Images.bioRxiv : the preprint server for biology · 2026Article
- Machine Learning in Stem Cell Research: From Biological Data to Clinical Translation.Computational and structural biotechnology journal · 2026Review
- Current status and future prospects of toxicity assessment using organoids.Toxicological research · 2025Review
- Using induced pluripotent stem cells for drug discovery in arrhythmias.Expert opinion on drug discovery · 2024Review
- A literature review: machine learning-based stem cell investigation.Annals of translational medicine · 2024Review
- AI-organoid integrated systems for biomedical studies and applications.Bioengineering & translational medicine · 2024Review
- Unlocking cardiac motion: assessing software and machine learning for single-cell and cardioid kinematic insights.Scientific reports · 2024Article
- The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review.PloS one · 2024Article
- BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs.IEEE open journal of engineering in medicine and biology · 2024Article
- Advances in physiological and clinical relevance of hiPSC-derived brain models for precision medicine pipelines.Frontiers in cellular neuroscience · 2024Review
- Current updates on arrhythmia within Timothy syndrome: genetics, mechanisms and therapeutics.Expert reviews in molecular medicine · 2023Review
- Rianú: Multi-tissue tracking software for increased throughput of engineered cardiac tissue screening.Computer methods and programs in biomedicine update · 2023Article
- Integrating nonlinear analysis and machine learning for human induced pluripotent stem cell-based drug cardiotoxicity testing.Journal of tissue engineering and regenerative medicine · 2022Article
- Induced Pluripotent Stem Cell-Based Drug Screening by Use of Artificial Intelligence.Pharmaceuticals (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 2 countries.
Funding
Abstract
Cardiomyocytes derived from human induced pluripotent stem (iPS) cells enable the study of cardiac physiology and the developmental testing of new therapeutic drugs in a human setting. In parallel, machine learning methods are being applied to biomedical science in unprecedented ways. Machine learning has been used to distinguish healthy from diseased cardiomyocytes using calcium (Ca
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.