Reinforcement Learning for Optimizing Personalized Treatment Plans in Oncology

Authors

  • Kushwanth Gondi Software Developer, Computer Science and Technology Company, USA,
  • Dedeepya Sai Gondi CTO/Director, Artificial Intelligence and Machine Learning Company, USA
  • Vamsi Krishna Reddy Bandaru Data Science Advisor, Artificial Intelligence and Machine Learning Company, USA
  • Veera Venkata Raghunath Indugu Engineer 1, Data Science and Cloud Technologies Company, USA
  • Hemanth Volikatla Independent Researcher, USA

Abstract

The application of reinforcement learning (RL) in healthcare has opened new avenues for personalized medicine. This 2021 study introduces a novel RL framework to optimize treatment plans for oncology patients. The RL agent learns from historical patient data, including treatment regimens, responses, and outcomes, to recommend personalized treatment strategies. The model was validated on a large dataset of breast cancer patients, showing a significant improvement in survival rates compared to standard treatment protocols. The study underscores the potential of RL in providing dynamic, patient-specific treatment recommendations that adapt to the evolving condition of patients.

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Published

2021-08-18

Issue

Vol. 4 No. 1 (2021): ACS 2021

Section

Articles