A brief review and scientometric analysis on ensemble learning methods for handling COVID-19

MJ Shayegan - Heliyon, 2024 - cell.com
Numerous efforts and research have been conducted worldwide to combat the coronavirus
disease 2019 (COVID-19) pandemic. In this regard, some researchers have focused on …

Computational cardiac physiology for new modelers: Origins, foundations, and future

JT Koivumäki, J Hoffman, MM Maleckar… - Acta …, 2022 - Wiley Online Library
Mathematical models of the cardiovascular system have come a long way since they were
first introduced in the early 19th century. Driven by a rapid development of experimental …

A literature embedding model for cardiovascular disease prediction using risk factors, symptoms, and genotype information

J Moon, HF Posada-Quintero, KH Chon - Expert Systems with Applications, 2023 - Elsevier
Accurate prediction of cardiovascular disease (CVD) requires multifaceted information
consisting of not only a patient's medical history, but genomic data, symptoms, lifestyle, and …

Identifying biomarkers for treatment of uveal melanoma by T cell engager using a QSP model

S Anbari, H Wang, T Arulraj, M Nickaeen… - npj Systems Biology …, 2024 - nature.com
Uveal melanoma (UM), the primary intraocular tumor in adults, arises from eye melanocytes
and poses a significant threat to vision and health. Despite its rarity, UM is concerning due to …

Recent advances in translational pharmacokinetics and pharmacodynamics prediction of therapeutic antibodies using modeling and simulation

K Haraya, H Tsutsui, Y Komori, T Tachibana - Pharmaceuticals, 2022 - mdpi.com
Therapeutic monoclonal antibodies (mAbs) have been a promising therapeutic approach for
several diseases and a wide variety of mAbs are being evaluated in clinical trials. To …

Combinatorial approaches for novel cardiovascular drug discovery: a review of the literature

S Brogi, R Tabanelli, V Calderone - Expert Opinion on Drug …, 2022 - Taylor & Francis
Introduction In this article, authors report an inclusive discussion about the combinatorial
approach for the treatment of cardiovascular diseases (CVDs) and for counteracting the …

Introduction to artificial intelligence for cardiovascular clinicians

AC Chang, A Limon - Intelligence-Based Cardiology and Cardiac Surgery, 2024 - Elsevier
The impressive gains in deep learning (DL) started in 2012 and its successful utilization in
image interpretation have led to the current momentum for artificial intelligence (AI) …

Data-driven discovery of dynamical systems in pharmacology using large language models

S Holt, Z Qian, T Liu, J Weatherall… - The Thirty-eighth …, 2024 - openreview.net
The discovery of dynamical systems is crucial across a range of fields, including
pharmacology, epidemiology, and physical sciences.* Accurate* and* interpretable …

Using machine learning surrogate modeling for faster QSP VP cohort generation

RC Myers, F Augustin, J Huard… - CPT: Pharmacometrics …, 2023 - Wiley Online Library
Virtual patients (VPs) are widely used within quantitative systems pharmacology (QSP)
modeling to explore the impact of variability and uncertainty on clinical responses. In one …

[HTML][HTML] Genetic data visualization using literature text-based neural networks: Examples associated with myocardial infarction

J Moon, HF Posada-Quintero, KH Chon - Neural Networks, 2023 - Elsevier
Data visualization is critical to unraveling hidden information from complex and high-
dimensional data. Interpretable visualization methods are critical, especially in the biology …