Redefining Mental Health Diagnostics and Algorithmic Innovation: Unifying AI in Depression Detection, Facial Recognition Efficiency, and Graph Coloring Solutions
DOI:
https://doi.org/10.70445/avjcs.2.1.2025.18-25Keywords:
Artificial Intelligence, Depression Detection, Facial Recognition, Machine Learning, Graph Coloring Algorithms, Mental Health Diagnostics, Emotion Recognition, Real-time Processing, Computational EfficiencyAbstract
At the beginning of the research the abstract introduces main goals, research methods, and projected achievements. The global healthcare system battles with depression as a major mental health concern because experts find it hard to find exact symptoms of this illness. Our study examines how Artificial Intelligence helps doctors make better depression diagnoses. The latest AI technology breakthroughs help medical experts go beyond standard diagnosis limitations by scanning faces and detecting emotional signals. Our standard identification technology now helps computers analyze facial expressions to spot sadness and fatigue alongside depression symptoms. Clinicians have trouble correctly reading emotional states in facial expressions without specific detection tools. This study applies graph coloring algorithms within artificial intelligence based medical diagnostic systems. This research uses optimization tools known as graph-coloring algorithms to improve AI systems that analyze large data sets efficiently. Our study combines artificial intelligence technology with facial recognition and graph coloring methods to create a complete system for better mental health diagnosis of depression.
References
1. Zainab H, Khan R, Khan AH, Hussain HK. REINFORCEMENT LEARNING IN CARDIOVASCULAR THERAPY PROTOCOL: A NEW PERSPECTIVE.
2. 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.
3. 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.
4. 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.
5. 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.
6. Sherani AM, Khan M. AI in Clinical Practice: Current Uses and the Path Forward. Global Journal of Universal Studies. 1(1):226-45.
7. 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
8. Calvo RA, Milne DN, Hussain MS, Christensen H. Natural language processing in mental health applications using non-clinical texts. Natural Language Engineering. 2017 Sep; 23(5):649-85.
9. 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.
10. 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
11. 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.
12. 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.
13. Abid N. Advancements and Best Practices in Data Loss Prevention: A Comprehensive Review. Global Journal of Universal Studies. 1(1):190-225.
14. 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.
15. Abid N. A Review of Security and Privacy Challenges in Augmented Reality and Virtual Reality Systems with Current Solutions and Future Directions.
16. 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.
17. 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.
18. 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.
19. 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.
20. 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.
21. 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.
22. 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.
23. 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.
24. Abid N. Empowering Cybersecurity: Optimized Network Intrusion Detection Using Data Balancing and Advanced Machine Learning Models.
25. 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.
26. 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.
27. 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.
28. 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.
29. 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.
30. 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.
31. 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.
32. 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.
33. Mehta A, Sambre T, Dayaramani R. ADVANCED ANALYTICAL TECHNIQUES FOR POST-TRANSLATIONAL MODIFICATIONS AND DISULFIDE LINKAGES IN BIOSIMILARS.
34. 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.
35. Abid N. Improving Accuracy and Efficiency of Online Payment Fraud Detection and Prevention with Machine Learning Models.
36. 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).
37. 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.
38. Wang X, Li X, Leung VC. Artificial intelligence-based techniques for emerging heterogeneous network: State of the arts, opportunities, and challenges. IEEE Access. 2015 Aug 11; 3:1379-91.
39. 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
40. Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, Aldairem A, Alrashed M, Bin Saleh K, Badreldin HA, Al Yami MS. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC medical education. 2023 Sep 22; 23(1):689.
41. 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
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.
