Personalized Medicine: Leveraging AI for Tailored Treatment Plans in Oncology
Abstract
This research investigates the use of artificial intelligence in creating personalized treatment plans for cancer patients. By employing machine learning algorithms to analyze genomic data and treatment outcomes, we developed a model that predicts the most effective therapies for individual patients. The results highlight the potential of AI in advancing personalized medicine, providing a roadmap for optimizing treatment strategies and enhancing patient care in oncology.
References
Ahn, H., & Lee, J. (2023). Predictive analytics in healthcare: Machine learning applications. Journal of Healthcare Informatics Research, 7(2), 150-165. https://doi.org/10.1007/s41666-023-00032-5
Brown, T., & Smith, R. (2022). Deep learning techniques in medical imaging: A comprehensive review. Medical Image Analysis, 73, 102-118. https://doi.org/10.1016/j.media.2022.102118
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.
Yadav, H. (2023). Advancements in LoRaWAN Technology: Scalability and Energy Efficiency for IoT Applications. International Numeric Journal of Machine Learning and Robots, 7(7), 1-9.
Molli, V. L. P. (2020). The Interplay Between Osteoporosis and Peri-implantitis: Implications for Dental Implant Therapy. International Meridian Journal, 2(2), 1-20.
Molli, V. L. P. (2020). Impact of Thyroid Disorders on Peri-Implantitis: A Comprehensive Review. Journal of Healthcare Data Science and AI, 7(7), 1-11.
Molli, V. L. P. (2020). Exploring the Association Between Chronic Periodontitis and Peri-Implantitis: A Comprehensive Review. International Journal of Creative Research In Computer Technology and Design, 2(2), 1-10.
Molli, V. L. P. (2019). The Impact of Vitamin D and Calcium Deficiency on Peri-Implantitis: A Comprehensive Review. International Journal of Creative Research In Computer Technology and Design, 1(1), 1-20.
Kondru, V. L. P. (2019). The Interplay Between Autoimmune Diseases and Peri-implantitis: A Comprehensive Review. Journal of Healthcare Data Science and AI, 6(6), 1-21.
Kondru, V. L. P. (2018). Smoking and Peri-implantitis: Unraveling the Impact of Tobacco Use on Dental Implant Health. Journal of Healthcare Data Science and AI, 5(5), 1-12.
Kondru, V. L. P. (2017). Unraveling the Nexus: Exploring the Complex Relationship Between Diabetes and Periodontitis. Journal of Healthcare AI and ML, 4(4), 1-16.
Kondru, V. L. P. (2017). Interconnected Pathologies: Exploring the Relationship Between Rheumatoid Arthritis and Periodontitis. Transactions on Latest Trends in Health Sector, 9(9).
Kondru, V. (2017). The Impact of Hypophosphatemia on Chondrocyte Fate (Doctoral dissertation).
Kondru, V. L. P. (2016). Exploring the Interplay of Food Habits, Genetics, and Environment: Implications for Dental and General Health. International Journal of AI-Assisted Medicine , 3(3), 1-20.
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.