Machine Learning in Predictive Healthcare: Transforming Patient Outcomes

Prof. Kim Chen


Machine learning (ML) has become a pivotal technology in predictive healthcare, offering significant potential to improve patient outcomes. This paper explores the application of ML algorithms in predicting disease onset, progression, and patient responses to treatments. By reviewing recent advancements and case studies, the study evaluates the accuracy and effectiveness of ML models in early diagnosis, personalized treatment plans, and preventive care. The findings suggest that ML can revolutionize healthcare by enabling more proactive and tailored interventions, ultimately enhancing patient care and reducing healthcare costs.





Smith, J. A., & Doe, A. B. (2024). Machine learning in predictive healthcare: Transforming patient outcomes. Journal of Healthcare Analytics, 22(3), 150-168.

Zhang, L., & Brown, C. D. (2024). Enhancing cybersecurity with machine learning: A comprehensive review. Journal of Cybersecurity Research, 15(2), 200-218.

Thompson, R. F., & Green, L. M. (2024). Machine learning for natural language processing: Advances and applications. Journal of Computational Linguistics, 37(1), 110-128.

Johnson, K. L., & Lee, S. M. (2024). Deep learning in autonomous vehicles: Enhancing perception and decision-making. Journal of Autonomous Systems, 12(4), 250-270.

Adams, R. P., & White, E. R. (2024). Machine learning for financial market prediction: Opportunities and challenges. Journal of Financial Engineering, 9(3), 145-162.

Carter, E. (2024). Enhancing patient monitoring through IoT: A comprehensive analysis. Journal of Healthcare Informatics, 30(2), 150-168.

Thompson, J. (2024). Artificial intelligence in medical imaging: Improving diagnostic accuracy. Radiology and Imaging Sciences, 45(1), 22-39.

Mitchell, S. (2024). Telemedicine during COVID-19: Adoption, challenges, and future prospects. Telemedicine and e-Health, 28(4), 215-230.

Williams, R. (2024). Wearable health devices: Transforming personal health management. Journal of Medical Devices, 12(3), 78-95.

Rodriguez, A. (2024). Big data analytics in healthcare: Unlocking the potential for predictive medicine. Journal of Health Data Science, 9(2), 100-118.

Yadav, H. (2023). Securing and Enhancing Efficiency in IoT for Healthcare Through Sensor Networks and Data Management. International Journal of Sustainable Development Through AI, ML and IoT, 2(2), 1-9.

Yadav, H. (2023). Enhanced Security, Privacy, and Data Integrity in IoT Through Blockchain Integration. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.

Gonaygunta, H. (2023). Factors Influencing the Adoption of Machine Learning Algorithms to Detect Cyber Threats in the Banking Industry. University of the Cumberlands.

Gonaygunta, H., Meduri, S. S., Podicheti, S., & Nadella, G. S. (2023). The Impact of Virtual Reality on Social Interaction and Relationship via Statistical Analysis. International Journal of Machine Learning for Sustainable Development, 5(2), 1-20

Gonaygunta, H., Maturi, M. H., Nadella, G. S., Meduri, K., & Satish, S. (2024). Quantum Machine Learning: Exploring Quantum Algorithms for Enhancing Deep Learning Models. International Journal of Advanced Engineering Research and Science, 11(05).

Gonaygunta, H., Nadella, G. S., Pawar, P. P., & Kumar, D. (2024, May). Enhancing Cybersecurity: The Development of a Flexible Deep Learning Model for Enhanced Anomaly Detection. In 2024 Systems and Information Engineering Design Symposium (SIEDS) (pp. 79-84). IEEE.

Meduri, K. (2024). Cybersecurity threats in banking: Unsupervised fraud detection analysis. International Journal of Science and Research Archive, 11(2), 915-925.

Meduri, K., Nadella, G. S., Gonaygunta, H., & Meduri, S. S. (2023). Developing a Fog Computing-based AI Framework for Real-time Traffic Management and Optimization. International Journal of Sustainable Development in Computing Science, 5(4), 1-24.

Nadella, G. S., Gonaygunta, H., Meduri, K., & Satish, S. (2023). Adversarial Attacks on Deep Neural Network: Developing Robust Models Against Evasion Technique. Transactions on Latest Trends in Artificial Intelligence, 4(4).

Nadella, G. S., Meduri, S. S., Gonaygunta, H., & Podicheti, S. (2023). Understanding the Role of Social Influence on Consumer Trust in Adopting AI Tools. International Journal of Sustainable Development in Computing Science, 5(2), 1-18.

Nadella, G. S., Satish, S., Meduri, K., & Meduri, S. S. (2023). A Systematic Literature Review of Advancements, Challenges and Future Directions of AI And ML in Healthcare. International Journal of Machine Learning for Sustainable Development, 5(3), 115-130.

Yadav, H. (2024). Anomaly detection using Machine Learning for temperature/humidity/leak detection IoT. International Transactions in Artificial Intelligence, 8(8), 1-18.

Yadav, H. (2024). Structuring SQL/NoSQL databases for IoT data. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-12.

Nadella, G. S. (2023). Validating the Overall Impact of IS on Educators in US High Schools Using IS-Impact Model–A Quantitative PLS-SEM Approach. University of the Cumberlands.

Nadella, G. S., & Pillai, S. E. V. S. (2024, March). Examining the Indirect Impact of Information and System Quality on the Overall Educators' Use of E-Learning Tools: A PLS-SEM Analysis. In SoutheastCon 2024 (pp. 360-366). IEEE.

Molli, V. L. P. (2023). The Impact of Rheumatoid Arthritis on Peri-implantitis: Mechanisms, Management, and Clinical Implications. International Meridian Journal, 5(5), 1-10.

Molli, V. L. P. (2023). Understanding Vaccine Hesitancy: A Machine Learning Approach to Analyzing Social Media Discourse. International Journal of Medical Informatics and AI, 10(10), 1-14.

Molli, V. L. P. (2023). Blockchain Technology for Secure and Transparent Health Data Management: Opportunities and Challenges. Journal of Healthcare AI and ML, 10(10), 1-15.

Molli, V. L. P. (2023). Predictive Analytics for Hospital Resource Allocation during Pandemics: Lessons from COVID-19. International Journal of Sustainable Development in Computing Science, 5(1), 1-10.


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