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.