AIMC Topic: Myocytes, Cardiac
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Two-Dimensional Deep Learning Frameworks for Drug-Induced Cardiotoxicity Detection.
ACS sensors
Jun 6, 2024
The identification of drug-induced cardiotoxicity remains a pressing challenge with far-reaching clinical and economic ramifications, often leading to patient harm and resource-intensive drug recalls. Current methodologies, including in vivo and in v...
Fillable Magnetic Microrobots for Drug Delivery to Cardiac Tissues In Vitro.
Advanced healthcare materials
May 29, 2024
Many cardiac diseases, such as arrhythmia or cardiogenic shock, cause irregular beating patterns that must be regulated to prevent disease progression toward heart failure. Treatments can include invasive surgery or high systemic drug dosages, which ...
Target Cell Extraction and Spectrum-Effect Relationship Coupled with BP Neural Network Classification for Screening Potential Bioactive Components in Ginseng Extract with a Protective Effect against Myocardial Damage.
Molecules (Basel, Switzerland)
Apr 28, 2024
Cardiovascular disease has become a common ailment that endangers human health, having garnered widespread attention due to its high prevalence, recurrence rate, and sudden death risk. Ginseng possesses functions such as invigorating vital energy, en...
A deep learning-based approach for efficient detection and classification of local Ca²⁺ release events in Full-Frame confocal imaging.
Cell calcium
Apr 24, 2024
The release of Ca ions from intracellular stores plays a crucial role in many cellular processes, acting as a secondary messenger in various cell types, including cardiomyocytes, smooth muscle cells, hepatocytes, and many others. Detecting and classi...
Integrated machine learning and multimodal data fusion for patho-phenotypic feature recognition in iPSC models of dilated cardiomyopathy.
Biological chemistry
Apr 24, 2024
Integration of multiple data sources presents a challenge for accurate prediction of molecular patho-phenotypic features in automated analysis of data from human model systems. Here, we applied a machine learning-based data integration to distinguish...
Neural network emulation of the human ventricular cardiomyocyte action potential for more efficient computations in pharmacological studies.
eLife
Apr 10, 2024
Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimen...
Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data.
Scientific reports
Mar 27, 2024
The detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological evaluation of induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs). We report that deep learning with a dataset that combines magnetic signa...
Analysis of cardiac single-cell RNA-sequencing data can be improved by the use of artificial-intelligence-based tools.
Scientific reports
Apr 26, 2023
Single-cell RNA sequencing (scRNAseq) enables researchers to identify and characterize populations and subpopulations of different cell types in hearts recovering from myocardial infarction (MI) by characterizing the transcriptomes in thousands of in...
Automated quantification and statistical assessment of proliferating cardiomyocyte rates in embryonic hearts.
American journal of physiology. Heart and circulatory physiology
Dec 23, 2022
The use of digital image analysis and count regression models contributes to the reproducibility and rigor of histological studies in cardiovascular research. The use of formalized computer-based quantification strategies of histological images essen...
A deep learning platform to assess drug proarrhythmia risk.
Cell stem cell
Dec 22, 2022
Drug safety initiatives have endorsed human iPSC-derived cardiomyocytes (hiPSC-CMs) as an in vitro model for predicting drug-induced cardiac arrhythmia. However, the extent to which human-defined features of in vitro arrhythmia predict actual clinica...
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