Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

M Alber, A Buganza Tepole, WR Cannon, S De… - NPJ digital …, 2019 - nature.com
Fueled by breakthrough technology developments, the biological, biomedical, and
behavioral sciences are now collecting more data than ever before. There is a critical need …

Precision medicine in human heart modeling: perspectives, challenges, and opportunities

M Peirlinck, FS Costabal, J Yao, JM Guccione… - … and modeling in …, 2021 - Springer
Precision medicine is a new frontier in healthcare that uses scientific methods to customize
medical treatment to the individual genes, anatomy, physiology, and lifestyle of each person …

Multiscale modeling meets machine learning: What can we learn?

GCY Peng, M Alber, A Buganza Tepole… - … Methods in Engineering, 2021 - Springer
Abstract Machine learning is increasingly recognized as a promising technology in the
biological, biomedical, and behavioral sciences. There can be no argument that this …

Predicting mechanically driven full-field quantities of interest with deep learning-based metamodels

S Mohammadzadeh, E Lejeune - Extreme Mechanics Letters, 2022 - Elsevier
Using simulation to predict the mechanical behavior of heterogeneous materials has
applications ranging from topology optimization to multi-scale structural analysis. However …

Prediction of arrhythmia susceptibility through mathematical modeling and machine learning

M Varshneya, X Mei, EA Sobie - Proceedings of the …, 2021 - National Acad Sciences
At present, the QT interval on the electrocardiographic (ECG) waveform is the most common
metric for assessing an individual's susceptibility to ventricular arrhythmias, with a long QT …

Synergy between machine learning and natural products cheminformatics: Application to the lead discovery of anthraquinone derivatives

S Moshawih, HP Goh, N Kifli, AC Idris… - Chemical Biology & …, 2022 - Wiley Online Library
Cheminformatics utilizing machine learning (ML) techniques have opened up a new horizon
in drug discovery. This is owing to vast chemical space expansion with rocketing numbers of …

MultiCBlo: Enhancing predictions of compound-induced inhibition of cardiac ion channels with advanced multimodal learning

T Wang, Z Du, L Zhuo, X Fu, Q Zou, X Yao - International journal of …, 2024 - Elsevier
Predicting compound-induced inhibition of cardiac ion channels is crucial and challenging,
significantly impacting cardiac drug efficacy and safety assessments. Despite the …

Enhancing mechanical metamodels with a generative model-based augmented training dataset

H Kobeissi, S Mohammadzadeh… - Journal of …, 2022 - asmedigitalcollection.asme.org
Modeling biological soft tissue is complex in part due to material heterogeneity.
Microstructural patterns, which play a major role in defining the mechanical behavior of …

Artificial intelligence in cardiovascular medicine

S Ranka, M Reddy, A Noheria - Current Opinion in Cardiology, 2021 - journals.lww.com
Artificial intelligence demonstrates the ability to learn through assimilation of large datasets
to unravel complex relationships, discover prior unfound pathophysiological states and …

Exploring the integration of informed machine learning in engineering applications: A comprehensive review

MA Bappy, M Ahmed, MA Rauf - Manam and Rauf, Md Abdur …, 2024 - papers.ssrn.com
Abstract Integrating Artificial Intelligence (AI) and Machine Learning (ML) into mechanical
engineering catalyzes a transformative shift within Industry 4.0, offering unprecedented …