Ki M. Lim
Gumi, Republic of Korea
Last Updated: 09/26/2026
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Found 77 publications
Cardiosim-Tox: an interpretable multitask deep learning QSAR platform with multimodal feature fusion for predicting hERG, Cav1.2, and Nav1.5 blockade risk and potency.
Journal: Archives of toxicology
Published: May 02, 2026
Improving biomarker robustness for in silico cardiac safety assessment through an excitation-contraction coupling model.
Journal: Toxicology and applied pharmacology
Published: April 20, 2026
ToxCML: A Hybrid mfCoQ-RASAR-Based Platform Integrating Consensus QSAR and Read-Across for Comprehensive Multi-End Point Toxicity Assessment.
Journal: Journal of chemical information and modeling
Published: April 13, 2026
Interpretable multi-modality consensus QSAR framework: integrating machine and deep learning for enhanced multi-endpoint toxicity assessment.
Journal: Toxicology mechanisms and methods
Published: March 17, 2026
Incorporating inter-individual variability to improve the reliability of predicted outcomes in in silico cardiac safety assessment.
Journal: Toxicology and applied pharmacology
Published: March 02, 2026
Integrating high-fidelity hiPSC-cardiomyocytes with AI-driven modeling for enhanced proarrhythmic risk assessment.
Journal: Archives of toxicology
Published: February 09, 2026
Improving In Silico Cardiac Safety Prediction by Consensus Averaging of Transmural Ventricular Cell Models.
Journal: Annals of biomedical engineering
Published: September 09, 2025
In silico cardiac safety assessment using a multi-biomarker approach based on an electrophysiological model of hiPSC-derived cardiomyocytes.
Journal: Toxicological research
Published: August 06, 2025
A machine learning platform for genotype-specific cardiotoxicity risk prediction using patient-derived iPSC-CMs.
Journal: Journal of advanced research
Published: May 11, 2025
A multiscale computational model of cardiac electrophysiology for drug-induced pro-arrhythmic risk stratification.
Journal: Biomedical engineering letters
Published: April 06, 2025
Advances in cardiovascular signal analysis with future directions: a review of machine learning and deep learning models for cardiovascular disease classification based on ECG, PCG, and PPG signals.
Journal: Biomedical engineering letters
Published: January 15, 2025
Validation of new AI-based classification method for in silico cardiac safety assessment of drugs following the CiPA framework.
Journal: Archives of toxicology
Published: December 12, 2024
Last Updated: 09/26/2026