BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs-Reference-Cited by-同舟云学术

BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs

Published:2024 Issue: Volume:5 Page:238-249
ISSN:2644-1276
Container-title:IEEE Open Journal of Engineering in Medicine and Biology
language:
Short-container-title:IEEE Open J. Eng. Med. Biol.

Author:

Kim Youngbin¹^ORCID,Wang Kunlun¹^ORCID,Lock Roberta I.¹,Nash Trevor R.¹^ORCID,Fleischer Sharon¹^ORCID,Wang Bryan Z.¹^ORCID,Fine Barry M.²^ORCID,Vunjak-Novakovic Gordana¹^ORCID

Affiliation:

1. Department of Biomedical Engineering, Columbia University, New York, NY, USA

2. Department of Medicine, Division of Cardiology, Columbia University Medical Center, New York, NY, USA

Funder

National Institutes of Health

National Science Foundation

National Aeronautics and Space Administration

Abramova Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/8782705/10443311/10490213-aam.pdf

Reference52 articles.

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2. Cardiac excitation–contraction coupling

3. Considerations for an In Vitro, Cell-Based Testing Platform for Detection of Drug-Induced Inotropic Effects in Early Drug Development. Part 2: Designing and Fabricating Microsystems for Assaying Cardiac Contractility With Physiological Relevance Using Human iPSC-Cardiomyocytes

4. MUSCLEMOTION

5. Image-based evaluation of contraction–relaxation kinetics of human-induced pluripotent stem cell-derived cardiomyocytes: Correlation and complementarity with extracellular electrophysiology

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