ArticleScientific reports2015
Machine learning plus optical flow: a simple and sensitive method to detect cardioactive drugs.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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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
27 citing papers in PubMed, 50 citations in OpenAlex.
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- Design optimization of geometrically confined cardiac organoids enabled by machine learning techniques.Cell reports methods · 2024Article
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- Advances in cardiac tissue engineering and heart-on-a-chip.Journal of biomedical materials research. Part A · 2024Review
- AI-organoid integrated systems for biomedical studies and applications.Bioengineering & translational medicine · 2024Review
- The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review.PloS one · 2024Article
- Beyond pharmaceuticals: Fit-for-purpose new approach methodologies for environmental cardiotoxicity testing.ALTEX · 2023Review
- 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
- Moving Towards Induced Pluripotent Stem Cell-based Therapies with Artificial Intelligence and Machine Learning.Stem cell reviews and reports · 2022Review
- Intersection of stem cell biology and engineering towards next generationFrontiers in bioengineering and biotechnology · 2022Review
- Machine Learning Techniques to Classify Healthy and Diseased Cardiomyocytes by Contractility Profile.ACS biomaterials science & engineering · 2021Article
- Cells/colony motion of oral keratinocytes determined by non-invasive and quantitative measurement using optical flow predicts epithelial regenerative capacity.Scientific reports · 2021Article
- Machine Learning in Arrhythmia and Electrophysiology.Circulation research · 2021Review
- SarcTrack.Circulation research · 2019Article
- Cardiac tissue engineering: state-of-the-art methods and outlook.Journal of biological engineering · 2019Review
- Manipulation-free cultures of human iPSC-derived cardiomyocytes offer a novel screening method for cardiotoxicity.Acta pharmacologica Sinica · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 1 country.
Funding
Abstract
Current preclinical screening methods do not adequately detect cardiotoxicity. Using human induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs), more physiologically relevant preclinical or patient-specific screening to detect potential cardiotoxic effects of drug candidates may be possible. However, one of the persistent challenges for developing a high-throughput drug screening platform using iPS-CMs is the need to develop a simple and reliable method to measure key electrophysiological and contractile parameters. To address this need, we have developed a platform that combines machine learning paired with brightfield optical flow as a simple and robust tool that can automate the detection of cardiomyocyte drug effects. Using three cardioactive drugs of different mechanisms, including those with primarily electrophysiological effects, we demonstrate the general applicability of this screening method to detect subtle changes in cardiomyocyte contraction. Requiring only brightfield images of cardiomyocyte contractions, we detect changes in cardiomyocyte contraction comparable to - and even superior to - fluorescence readouts. This automated method serves as a widely applicable screening tool to characterize the effects of drugs on cardiomyocyte function.
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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.