AIMC Topic: Cardiotoxicity

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A deep-learning semantic segmentation approach to fully automated MRI-based left-ventricular deformation analysis in cardiotoxicity.

Magnetic resonance imaging
Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to breast cancer chemotherapy. This study investigated an automated LV ch...

Machine Learning-Based Risk Assessment for Cancer Therapy-Related Cardiac Dysfunction in 4300 Longitudinal Oncology Patients.

Journal of the American Heart Association
Background The growing awareness of cardiovascular toxicity from cancer therapies has led to the emerging field of cardio-oncology, which centers on preventing, detecting, and treating patients with cardiac dysfunction before, during, or after cancer...

Prediction of hERG potassium channel blockage using ensemble learning methods and molecular fingerprints.

Toxicology letters
The human ether-a-go-go-related gene (hERG) encodes a tetrameric potassium channel called Kv11.1. This channel can be blocked by certain drugs, which leads to long QT syndrome, causing cardiotoxicity. This is a significant problem during drug develop...

Machine-learning-based quality control of contractility of cultured human-induced pluripotent stem-cell-derived cardiomyocytes.

Biochemical and biophysical research communications
The precise and early assessment of cardiotoxicity is fundamental to bring forward novel drug candidates to the pharmaceutical market and to avoid their withdrawal from the market. Recent preclinical studies have attempted to use human-induced plurip...

Effect of Radiation Doses to the Heart on Survival for Stereotactic Ablative Radiotherapy for Early-stage Non-Small-cell Lung Cancer: An Artificial Neural Network Approach.

Clinical lung cancer
INTRODUCTION: The cardiac radiation dose is an important predictor of cardiac toxicity and overall survival (OS) for patients with locally advanced non-small-cell lung cancer (NSCLC). However, radiation-induced cardiac toxicity among patients with ea...

Computational determination of hERG-related cardiotoxicity of drug candidates.

BMC bioinformatics
BACKGROUND: Drug candidates often cause an unwanted blockage of the potassium ion channel of the human ether-a-go-go-related gene (hERG). The blockage leads to long QT syndrome (LQTS), which is a severe life-threatening cardiac side effect. Therefore...

Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity.

Journal of chemical information and modeling
Blockade of the human ether-à-go-go-related gene (hERG) channel by small molecules induces the prolongation of the QT interval which leads to fatal cardiotoxicity and accounts for the withdrawal or severe restrictions on the use of many approved drug...

Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification.

Stem cell reports
Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-deriv...

AI-Assisted Hypothesis Generation to Address Challenges in Cardiotoxicity Research: Simulation Study Using ChatGPT With GPT-4o.

Journal of medical Internet research
BACKGROUND: Cardiotoxicity is a major concern in heart disease research because it can lead to severe cardiac damage, including heart failure and arrhythmias.

Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy-Related Cardiovascular Toxicity: Systematic Review.

JMIR cancer
BACKGROUND: Artificial intelligence (AI) is a revolutionary tool yet to be fully integrated into several health care sectors, including medical imaging. AI can transform how medical imaging is conducted and interpreted, especially in cardio-oncology.