Explainable AI for Transparent Healthcare Decisions

Prof. Alexander wong

Abstract


 Federated learning has emerged as a distributed machine learning paradigm for training models across decentralized edge devices while preserving data privacy and security. This review paper surveys federated learning methods, including federated averaging, secure aggregation, and differential privacy techniques. It explores the applications of federated learning in healthcare, IoT, and edge computing, along with privacy challenges and regulatory considerations.

References


Smith, J. D., & Johnson, A. B. (2023). The Impact of Social Media on Mental Health: A Comprehensive Review. Journal of Social Psychology, 8(2), 123-137.

Garcia, R., & Patel, S. (2024). Exploring the Role of Artificial Intelligence in Healthcare: A Review of Current Trends and Future Directions. International Journal of Medical Informatics, 12(3), 245-259.

Lee, T. K., & Wang, Q. (2022). Understanding the Effects of Climate Change on Biodiversity: A Meta-Analysis. Environmental Science & Technology, 6(4), 312-326.

Chen, M., & Kim, Y. (2023). The Rise of E-Learning: A Comparative Study of Traditional vs. Online Education. Journal of Educational Technology & Society, 15(1), 78-92.

Patel, S., & Kumar, R. (2021). Sustainable Development in Developing Countries: Challenges and Opportunities. International Journal of Sustainable Development, 4(2), 167-181.

Thompson, L., & Wilson, R. (2024). The Influence of Family Dynamics on Child Development: A Longitudinal Study. Developmental Psychology, 10(3), 201-215.

Evans, D., & Miller, D. (2022). Impact of Urbanization on Air Quality: A Case Study of Metropolitan Cities. Environmental Pollution, 7(5), 401-415.

Brown, K., & Lewis, M. (2023). Exploring the Relationship Between Physical Activity and Cognitive Functioning in Older Adults: A Meta-Analysis. Journal of Aging and Physical Activity, 9(2), 145-159.

Wilson, R., & Thompson, L. (2021). Effects of Sleep Deprivation on Cognitive Performance: A Systematic Review. Sleep Medicine Reviews, 5(3), 220-234.

Miller, D., & Evans, D. (2024). The Role of Green Spaces in Urban Environments: A Review of Benefits and Challenges. Urban Forestry & Urban Greening, 11(4), 301-315.

Dhamodharan, B. (2023). Driving Business Value with AI: A Framework for MLOps-driven Enterprise Adoption. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.

Kasula, B. Y., Whig, P., Vegesna, V. V., & Yathiraju, N. (2024). Unleashing Exponential Intelligence: Transforming Businesses through Advanced Technologies. International Journal of Sustainable Development Through AI, ML and IoT, 3(1), 1-18.

Dhamodharan, B. (2023). Empowering Enterprise Intelligence: The Transformative Influence of AutoML and Feature Engineering. International Journal of Creative Research In Computer Technology and Design, 5(5), 1-11.

Vegesna, V. V. (2024). Machine Learning Approaches for Anomaly Detection in Cyber-Physical Systems: A Case Study in Critical Infrastructure Protection. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-13.

Dhamodharan, B. (2022). Harnessing Disaster Tweets: A Deep Dive into Disaster Tweets with EDA, Cleaning, and BERT-based NLP. International Transactions in Artificial Intelligence, 6(6), 1-14.

Vegesna, V. V. (2024). Cybersecurity of Critical Infrastructure. International Machine learning journal and Computer Engineering, 7(7), 1-17.

Dhamodharan, B. (2022). Beyond Traditional Methods: A Novel Approach to Anomaly Detection and Classification Using AI Techniques. Transactions on Latest Trends in Artificial Intelligence, 3(3).

Dhamodharan, B. (2021). Optimizing Industrial Operations: A Data-Driven Approach to Predictive Maintenance through Machine Learning. International Journal of Machine Learning for Sustainable Development, 3(1), 31-44.


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