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Deep Learning and Optimization Insight into Cardiovascular Risk Factors, Cognitive Decline

Journal: Brain & Heart
Submission deadline: 20 August 2024
Special Issue Editors
Saurav Mallik
Department of Pharmacology and Toxicology, The University of Arizona, USA
Interests: Data mining, computational biology, bioinformatics, Bio-statistics, machine learning
Mathivanan Sandeep Kumar
School of Computing Science & Engineering, Galgotias University, Greater Noida, India
Interests: Artificial Intelligence; Block Chain; Computational Biology; Data Mining; Bio-statistics; Machine Learning
Guimin Qin
School of Computer Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China
Interests: Bioinformatics; machine learning; computational biology; system biology
S.K.B Sangeetha
Department of Computer Science and Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, India
Interests: Data analytics, Machine Learning, Deep Learning
Special Issue Information

This Special issue represents a pioneering exploration at the crossroads of deep learning/machine learning/optimization and healthcare, focusing on unraveling the intricate connection between cardiovascular risk factors and cognitive decline. It delves into the application of several advanced computational mechanisms, especially, deep learning (DL), machine learning (ML) and optimization algorithms, to decode the complex patterns and correlations within the high-throughput datasets related to the health of the heart and cognitive function. Through the lens of medical imaging, predictive modeling, next generation data analysis, natural language processing, and longitudinal data analysis, the special issue illuminates how machine learning, deep learning and optimization unveil the subtle biomarkers/genetic signatures, identifies predictive relationships, and enhances our understanding of the interplay between cardiovascular risk factors and cognitive decline. By harnessing these insights, the special issue envisions a future of more accurate risk prediction, tailored interventions, and enhanced management strategies, offering promising pathways to mitigate cognitive decline associated with cardiovascular health issues along with cancer.

Deep Learning;
Cardiovascular Health
Predictive Modeling
Medical Imaging
Personalized Interventions
Next generation sequencing data
Gene signature and cancer marker identification
Published Paper (1 Paper)

Recognition predictive modeling using electroencephalogram

S.K.B. Sangeetha, Sandeep Kumar Mathivanan, Saurav Mallik, Aimin Li
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Brain & Heart, Electronic ISSN: 2972-4139 Published by AccScience Publishing