Synergizing AI for Cognitive Insights, Visual Pattern Recognition, and Computational Advancements: A Novel Exploration of EEG Detection, Deep Learning, and Cat Swarm Optimization
DOI:
https://doi.org/10.70445/avjcs.2.1.2025.26-36Keywords:
Artificial Intelligence, EEG Detection, Deep Learning, Visual Pattern Recognition, Cat Swarm Optimization, Cognitive Insights, Neurotherapy, Optimization TechniquesAbstract
AI integration with cognitive science helps scientists develop better methods to read brain activity signals and recognize visual patterns plus optimize computing tasks. Our study develops a new cognitive approach which integrates deep learning algorithms with both visual pattern recognition and cat swarm optimization to improve data analysis speeds. The suggested framework joins different fields to combat EEG noise issues and fix issues with standard pattern recognition and suboptimal optimization solutions. The study tests this method's success in healthcare services and shows its benefits for computer thinking and robot applications.
References
1. Abibullaev B, Keutayeva A, Zollanvari A. Deep learning in EEG-based BCIs: a comprehensive review of transformer models, advantages, challenges, and applications. IEEE Access. 2023 Nov 2.
2. Khan AH, Zainab H, Khan R, Hussain HK. Deep Learning in the Diagnosis and Management of Arrhythmias. Journal of Social Research. 2024 Dec 6;4(1):50-66.
3. Choudhary V, Patel K, Niaz M, Panwala M, Mehta A, Choudhary K. Implementation of Next-Gen IoT to Facilitate Strategic Inventory Management System and Achieve Logistics Excellence. In2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024 Mar 22 (pp. 1-6). IEEE.
4. Khan M, Shiwlani A, Qayyum MU, Sherani AM, Hussain HK. Revolutionizing Healthcare with AI: Innovative Strategies in Cancer Medicine. International Journal of Multidisciplinary Sciences and Arts. 2024 May 26; 3(1):316-24.
5. Khan, A. H., Zainab, H., Khan, R., & Hussain, H. K. (2024). Implications of AI on Cardiovascular Patients ‘Routine Monitoring and Telemedicine. BULLET: Jurnal Multidisiplin Ilmu, 3(5), 621-637.
6. Abid N. Enhanced IoT Network Security with Machine Learning Techniques for Anomaly Detection and Classification. Int. J. Curr. Eng. Technol. 2023;13(6):536-44.
7. Mehta A, Sambre T, Dayaramani R. ADVANCED ANALYTICAL TECHNIQUES FOR POST-TRANSLATIONAL MODIFICATIONS AND DISULFIDE LINKAGES IN BIOSIMILARS.
8. Yang X. Machine Vision Technologies for Evaluating Key Production and Welfare Indicators of Cage-Free Layers (Doctoral dissertation, University of Georgia).
9. Saeed, A., Husnain, A., Zahoor, A., & Gondal, R. M. (2024). A comparative study of cat swarm algorithm for graph coloring problem: Convergence analysis and performance evaluation. International Journal of Innovative Research in Computer Science and Technology (IJIRCST), 12(4), 1-9. https://doi.org/10.55524/ijircst.2024.12.4.1
10. Husnain, A., & Saeed, A. (2024). AI-enhanced depression detection and therapy: Analyzing the VPSYC system. IRE Journals, 8(2), 162-168. https://doi.org/IRE1706118
11. Husnain, A., Alomari, G., & Saeed, A. (2024). AI-driven integrated hardware and software solution for EEG-based detection of depression and anxiety. International Journal for Multidisciplinary Research (IJFMR), 6(3), 1-24. https://doi.org/10.30574/ijfmr.2024.v06i03.22645
12. Chen, JJ., Husnain, A., Cheng, WW. (2024). Exploring the Trade-Off Between Performance and Cost in Facial Recognition: Deep Learning Versus Traditional Computer Vision. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2023. Lecture Notes in Networks and Systems, vol 823. Springer, Cham. https://doi.org/10.1007/978-3-031-47724-9_27
13. Venugopal K, Jagadeesh B. Theoretical Insights Into User Security and Privacy in Social. Human Impact on Security and Privacy: Network and Human Security, Social Media, and Devices: Network and Human Security, Social Media, and Devices. 2024 Oct 3:289.
14. Umar, M., Shiwlani, A., Saeed, F., Ahmad, A., Ali, M. H., & Shah, A. T. (2023). Role of deep learning in diagnosis, treatment, and prognosis of oncological conditions. International Journal, 10(5), 1059-1071.
15. Shiwlani, A., Ahmad, A., Umar, M., Dharejo, N., Tahir, A., & Shiwlani, S. (2024). BI-RADS category prediction from mammography images and mammography radiology reports using deep learning: A systematic review. Jurnal Ilmiah Computer Science, 3(1), 30-49.
16. Jahangir, Z., Saeed, F., Shiwlani, A., Shiwlani, S., & Umar, M. (2024). Applications of ML and DL algorithms in the prediction, diagnosis, and prognosis of Alzheimer’s disease. American Journal of Biomedical Science & Research, 22(6), 779-786.
17. Shiwlani, A., Ahmad, A., Umar, M., Dharejo, N., Tahir, A., & Shiwlani, S. (2024). Analysis of multi-modal data through deep learning techniques to diagnose CVDs: A review. International Journal, 11(1), 402-420.
18. Abid N. Advancements and Best Practices in Data Loss Prevention: A Comprehensive Review. Global Journal of Universal Studies. 1(1):190-225.
19. Khan MI, Arif A, Khan AR. AI-Driven Threat Detection: A Brief Overview of AI Techniques in Cybersecurity. BIN: Bulletin of Informatics. 2024; 2(2):248-61.
20. Milson S, Altan D. Synergizing AI and Big Data: Innovations in Smart Decision Making. EasyChair; 2024 Jan 4.
21. Abid N. A Review of Security and Privacy Challenges in Augmented Reality and Virtual Reality Systems with Current Solutions and Future Directions.
22. Qayyum MU, Sherani AM, Khan M, Hussain HK. Revolutionizing Healthcare: The Transformative Impact of Artificial Intelligence in Medicine. BIN: Bulletin of Informatics. 2023; 1(2):71-83.
23. Singh A, Randive S, Breggia A, Ahmad B, Christman R, Amal S. Enhancing Prostate Cancer Diagnosis with a Novel Artificial Intelligence-Based Web Application: Synergizing Deep Learning Models, Multimodal Data, and Insights from Usability Study with Pathologists. Cancers. 2023 Nov 30;15(23):5659.
24. Arif A, Khan A, Khan MI. Role of AI in Predicting and Mitigating Threats: A Comprehensive Review. JURIHUM: Jurnal Inovasi dan Humaniora. 2024; 2(3):297-311.
25. Khan M, Shiwlani A, Qayyum MU, Sherani AM, Hussain HK. AI-powered healthcare revolution: an extensive examination of innovative methods in cancer treatment. BULLET: Jurnal Multidisiplin Ilmu. 2024 Feb 28; 3(1):87-98.
26. Sherani AM, Khan M, Qayyum MU, Hussain HK. Synergizing AI and Healthcare: Pioneering Advances in Cancer Medicine for Personalized Treatment. International Journal of Multidisciplinary Sciences and Arts. 2024 Feb 4; 3(1):270-7.
27. Abid N. Securing Financial Systems with Block chain: A Comprehensive Review of Block chainand Cybersecurity Practices. International Journal of Multidisciplinary Sciences and Arts. 3(4):193-205.
28. MEHTA A, CHOUDHARY V, NIAZ M, NWAGWU U. Artificial Intelligence Chatbots and Sustainable Supply Chain Optimization in Manufacturing: Examining the Role of Transparency. Innovativeness, and Industry. 2023 Jul; 4.
29. Khan MI, Arif A, Khan A. AI's Revolutionary Role in Cyber Defense and Social Engineering. International Journal of Multidisciplinary Sciences and Arts. 2024;3(4):57-66.
30. MEHTA A, CHOUDHARY V, NIAZ M, NWAGWU U. Artificial Intelligence Chatbots and Sustainable Supply Chain Optimization in Manufacturing: Examining the Role of Transparency. Innovativeness, and Industry. 2023 Jul; 4.
31. Abid N. Empowering Cybersecurity: Optimized Network Intrusion Detection Using Data Balancing and Advanced Machine Learning Models.
32. Umar, M., Shiwlani, A., Saeed, F., Ahmad, A., Ali, M. H., & Shah, A. T. (2023). Role of deep learning in diagnosis, treatment, and prognosis of oncological conditions. International Journal, 10(5), 1059-1071.
33. Khan MI, Arif A, Khan AR. The Most Recent Advances and Uses of AI in Cybersecurity. BULLET: Jurnal Multidisiplin Ilmu. 2024; 3(4):566-78.
34. Qayyum MU, Sherani AM, Khan M, Hussain HK. Revolutionizing Healthcare: The Transformative Impact of Artificial Intelligence in Medicine. BIN: Bulletin of Informatics. 2023; 1(2):71-83.
35. Zainab H, Khan R, Khan AH, Hussain HK. REINFORCEMENT LEARNING IN CARDIOVASCULAR THERAPY PROTOCOL: A NEW PERSPECTIVE.
36. Choudhary V, Patel K, Niaz M, Panwala M, Mehta A, Choudhary K. Risk Management Strategies for Biotech Startups: A Comprehensive Framework for Early-Stage Projects. InRecent Trends In Engineering and Science for Resource Optimization and Sustainable Development 2024 (pp. 448-456). CRC Press.
37. Khan R, Zainab H, Khan AH, Hussain HK. Advances in Predictive Modeling: The Role of Artificial Intelligence in Monitoring Blood Lactate Levels Post-Cardiac Surgery. International Journal of Multidisciplinary Sciences and Arts. 2024; 3(4):140-51.
38. Sherani AM, Qayyum MU, Khan M, Shiwlani A, Hussain HK. Transforming Healthcare: The Dual Impact of Artificial Intelligence on Vaccines and Patient Care. BULLET: Jurnal Multidisiplin Ilmu. 2024 May 27; 3(2):270-80.
39. Arif A, Khan MI, Khan A. An overview of cyber threats generated by AI. International Journal of Multidisciplinary Sciences and Arts. 2024; 3(4):67-76.
40. Sherani AM, Khan M. AI in Clinical Practice: Current Uses and the Path Forward. Global Journal of Universal Studies. 1(1):226-45.
41. Qayyum MU, Sherani AM, Khan M, Shiwlani A, Hussain HK. Using AI in Healthcare to Manage Vaccines Effectively. JURIHUM: Jurnal Inovasi dan Humaniora. 2024 May 27; 1(6):841-54.
42. Abid N. Improving Accuracy and Efficiency of Online Payment Fraud Detection and Prevention with Machine Learning Models.
43. Mehta A, Patel N, Joshi R. Method Development and Validation for Simultaneous Estimation of Trace Level Ions in Purified Water by Ion Chromatography. Journal of Pharmaceutical and Medicinal Chemistry. 2024 Jan; 10(1).
44. Shah HH. Advancements in Machine Learning Algorithms: Creating a New Era of Professional Predictive Analytics for Increased Effectiveness of Decision Making.
45. Zhang R. Synergizing Neuroscience and Artificial Intelligence: Brain-Inspired Architectures for Enhanced Performance and Neural Computation Insights (Doctoral dissertation, New York University Tandon School of Engineering).
Downloads
Published
Issue
Section
License
Copyright (c) 2025 AlgoVista: Journal of AI & Computer Science
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish in this journal agree to the following terms:
- Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
