Integrating Deep Learning to Decode Meningeal Interleukin-17 T Cell Mechanisms in Salt-Sensitive Hypertension-Induced Cognitive Impairment

• Published in: 2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0 pp. 1 - 6
• Main Authors: Tiwari, Shikha, Kashyap, Ramgopal, Roy, Vandana
• Format: Conference Proceeding
• Language: English
• Published: IEEE 05-06-2024
• Subjects: Accuracy; Biological system modeling; Brain modeling; Cells (biology); Cognitive Impairment; Computational modeling; Deep learning; Hypertension; Interleukin-17 T Cells; Meningeal; Molecular Mechanisms; Neurobiology; Reviews; Salt-Sensitive; Therapeutic Interventions
• DOI: 10.1109/OTCON60325.2024.10687585

This article uses deep learning to explain how salt-responsive meningeal interleukin-17 T cells produce cognitive impairment from elevated blood pressure. The proposed method combines attention processes with carefully selected biological indicators to simplify and improve information. Using complete performance research and proven deep learning algorithms, the proposed method outperforms competitors in accuracy and training time. A detailed ablation investigation shows how attention processes and biological indicators affect model performance. Notably, the research identifies a tiny trade-off between model complexity and computer performance that can improve real-world operations. The suggested strategy benefits from being understandable, especially in biological situations where straightforward decision-making is crucial. The ablation investigation illustrates how attention processes simplify things and suggests model improvements. To conclude, deep learning simplifies the complex biochemical networks connected to cognitive impairment in high blood pressure patients. The recommended approach, which has been tested via rigorous assessments and ablation testing, is robust and intelligible, helps us understand how high blood pressure affects cognitive function, and allows for more targeted treatment.