Harnessing AI for advancements in cardiovascular disease management and drug discovery

Ayesha Saeed 1, *, Ahsan Ahmad 2 and Ali Husnain 3

1 Department of Computer Science, University of Lahore, Pakistan.
2 Department of Computer Science, DePaul University Chicago, USA.
3 Department of Computer Science, University of Chicago, USA.
 
Review
International Journal of Science and Research Archive, 2024, 13(01), 244–249.
Article DOI: 10.30574/ijsra.2024.13.1.1623
Publication history: 
Received on 22 July 2024; revised on 01 September 2024; accepted on 03 September 2024
 
Abstract: 
The integration of artificial intelligence (AI) in cardiovascular disease (CVD) management and drug discovery has revolutionized clinical decision-making, offering new avenues for precision medicine and enhanced patient care. This study explores the long-term use of cardiovascular drugs and the role of AI in improving diagnosis, risk prediction, and therapeutic outcomes. While traditional clinical trials often lack extensive follow-up data, particularly concerning the elderly, AI models provide opportunities to fill these gaps through the analysis of large datasets. The research methodology employed in this study involves comprehensive data collection from clinical and biomedical sources, AI model development, rigorous validation, and ethical considerations, ensuring reliable and actionable insights. The findings underscore the potential of AI to transform CVD management and drug discovery, while also highlighting the need for continuous learning and ethical deployment to address challenges such as data privacy and algorithmic transparency.
 
Keywords: 
Cardiovascular; Hyperparameter; Convolutional Neural Networks; AI; Disease detection; GDPR
 
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