AIMC Topic: Cardiotoxicity

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Research Priorities and Future Directions in Cardio-Oncology.

Current treatment options in oncology
The subspecialty of cardio-oncology has undergone significant growth in recent years, alongside major advances in the management of both cardiovascular disease and cancer, the leading causes of morbidity and mortality in the United States and many co...

Cardiovascular Care in Pediatric Cancer Survivors: Updates on Risk, Prevention, and Therapies.

Current treatment options in oncology
Improved survival in pediatric oncology has highlighted the growing burden of cancer treatment-related cardiotoxicity among survivors of childhood cancers. While the cardiotoxicity of anthracyclines and chest radiation are well documented as major co...

Radiomics early assessment of post chemotherapy cardiotoxicity in cancer patients using 2D echocardiography imaging an interpretable machine learning study.

Scientific reports
Cardiotoxicity is the loss of the heart muscle's ability to contract effectively, often due to chemotherapy or radiation therapy. This study uses interpretable machine learning to predict post-chemotherapy cardiotoxicity using radiomics features extr...

Artificial Intelligence for Identification of Patients with Increased Risk of Severe Cancer Therapy-Related Cardiac Dysfunction Following Anthracycline Therapy.

The American journal of medicine
BACKGROUND: Early detection of cancer therapy-related cardiac dysfunction (CTRCD) after anthracycline exposure is critically important in minimizing morbidity and mortality. Artificial intelligence models applied to electrocardiograms (ECG-AI) may al...

DICTrank Is a Reliable Dataset for Cardiotoxicity Prediction Using Machine Learning Methods.

Chemical research in toxicology
Drug-induced cardiotoxicity (DICT) is a significant challenge in drug development and public health. DICT can arise from various mechanisms; New Approach Methods (NAMs), including quantitative structure-activity relationships (QSARs), have been exten...

MultiCTox: Empowering Accurate Cardiotoxicity Prediction through Adaptive Multimodal Learning.

Journal of chemical information and modeling
Cardiotoxicity refers to the inhibitory effects of drugs on cardiac ion channels. Accurate prediction of cardiotoxicity is crucial yet challenging, as it directly impacts the evaluation of cardiac drug efficacy and safety. Numerous methods have been ...

GraphDeep-hERG: Graph Neural Network PharmacoAnalytics for Assessing hERG-Related Cardiotoxicity.

Pharmaceutical research
PURPOSE: The human Ether-a-go-go Related-Gene (hERG) encodes rectifying potassium channels that play a significant role during action potential repolarization of cardiomyocytes. Blockade of the hERG channel by off-target drugs can lead to long QT syn...

CardiOT: Towards Interpretable Drug Cardiotoxicity Prediction Using Optimal Transport and Kolmogorov--Arnold Networks.

IEEE journal of biomedical and health informatics
Investigating the inhibitory effects of compounds on cardiac ion channels is essential for assessing cardiac drug safety. Consequently, researchers have developed computational models to evaluate combined cardiotoxicity (CCT) on cardiac ion channels....

Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association.

Circulation. Genomic and precision medicine
Artificial intelligence is poised to transform cardio-oncology by enabling personalized care for patients with cancer, who are at a heightened risk of cardiovascular disease due to both the disease and its treatments. The rising prevalence of cancer ...