Keywords
Treatment Plans
How to Cite
Abstract
The treatment of patients historically relies on the use of medicines that work best for the larger population but could have variable effects or adverse reactions in some individuals. The release of such drugs has justified the use of a one-size-fits-all approach, where the prescription decision is not individualized based on patient characteristics. A paradigm shift in healthcare is observed when the most effective therapeutic strategies for specific patient populations are designed. The convergence of genetic variation, clinical features, and lifestyle factors provides the biggest promise for increasing therapeutic efficacy and patient safety in recent years. This has encouraged the initiation and provision of data and clinical trial arms to treat the affected populations. The application of AI in analyzing these multilevel data to find the hidden patterns, novel connections, and actionable insights may aid in the prior and custom therapeutic strategy.
References
Gadhiraju, Asha, and Kummaragunta Joel Prabhod. "Reinforcement Learning for Optimizing Surgical Procedures and Patient Recovery." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 105-140.
Pushadapu, Navajeevan. "The Importance of Remote Clinics and Telemedicine in Healthcare: Enhancing Access and Quality of Care through Technological Innovations." Asian Journal of Multidisciplinary Research & Review 1.2 (2020): 215-261.
Potla, Ravi Teja. "AI and Machine Learning for Enhancing Cybersecurity in Cloud-Based CRM Platforms." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 287-302.
Thatoi, Priyabrata, et al. "Natural Language Processing (NLP) in the Extraction of Clinical Information from Electronic Health Records (EHRs) for Cancer Prognosis." International Journal 10.4 (2023): 2676-2694.
Bao, Y.; Qiao, Y.; Choi, J.E.; Zhang, Y.; Mannan, R.; Cheng, C.; He, T.; Zheng, Y.; Yu, J.; Gondal, M.; et al. Targeting the lipid kinase PIKfyve upregulates surface expression of MHC class I to augment cancer immunotherapy. Proc. Natl. Acad. Sci. USA 2023, 120, e2314416120.
Krothapalli, Bhavani, Lavanya Shanmugam, and Jim Todd Sunder Singh. "Streamlining Operations: A Comparative Analysis of Enterprise Integration Strategies in the Insurance and Retail Industries." Journal of Science & Technology 2.3 (2021): 93-144.
Gayam, Swaroop Reddy. "Artificial Intelligence for Natural Language Processing: Techniques for Sentiment Analysis, Language Translation, and Conversational Agents." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 175-216.
Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Compliance and Regulatory Reporting in Banking: Advanced Techniques, Models, and Real-World Applications." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 151-189.
Putha, Sudharshan. "AI-Driven Natural Language Processing for Voice-Activated Vehicle Control and Infotainment Systems." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 255-295.
Sahu, Mohit Kumar. "Machine Learning Algorithms for Personalized Financial Services and Customer Engagement: Techniques, Models, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 272-313.
Kasaraneni, Bhavani Prasad. "Advanced Machine Learning Models for Risk-Based Pricing in Health Insurance: Techniques and Applications." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 170-207.
Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Models for Predictive Analytics in Insurance: Techniques, Applications, and Real-World Case Studies." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 244-290.
Devan, Munivel, Bhavani Krothapalli, and Mahendher Govindasingh Krishnasingh. "Hybrid Cloud Data Integration in Retail and Insurance: Strategies for Seamless Interoperability." Journal of Artificial Intelligence Research 3.2 (2023): 103-145.
Kasaraneni, Ramana Kumar. "AI-Enhanced Pharmacoeconomics: Evaluating Cost-Effectiveness and Budget Impact of New Pharmaceuticals." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 291-327.
Pattyam, Sandeep Pushyamitra. "AI-Driven Data Science for Environmental Monitoring: Techniques for Data Collection, Analysis, and Predictive Modeling." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 132-169.
Kuna, Siva Sarana. "Reinforcement Learning for Optimizing Insurance Portfolio Management." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 289-334.
Prabhod, Kummaragunta Joel. "The Role of Machine Learning in Genomic Medicine: Advancements in Disease Prediction and Treatment." Journal of Deep Learning in Genomic Data Analysis 2.1 (2022): 1-52.
Pushadapu, Navajeevan. "Optimization of Resources in a Hospital System: Leveraging Data Analytics and Machine Learning for Efficient Resource Management." Journal of Science & Technology 1.1 (2020): 280-337.
Potla, Ravi Teja. "Integrating AI and IoT with Salesforce: A Framework for Digital Transformation in the Manufacturing Industry." Journal of Science & Technology 4.1 (2023): 125-135.
Gayam, Swaroop Reddy, Ramswaroop Reddy Yellu, and Praveen Thuniki. "Artificial Intelligence for Real-Time Predictive Analytics: Advanced Algorithms and Applications in Dynamic Data Environments." Distributed Learning and Broad Applications in Scientific Research 7 (2021): 18-37.
Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Customer Behavior Analysis in Insurance: Advanced Models, Techniques, and Real-World Applications." Journal of AI in Healthcare and Medicine 2.1 (2022): 227-263.
Putha, Sudharshan. "AI-Driven Personalization in E-Commerce: Enhancing Customer Experience and Sales through Advanced Data Analytics." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 225-271.
Sahu, Mohit Kumar. "Machine Learning for Personalized Insurance Products: Advanced Techniques, Models, and Real-World Applications." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 60-99.
Kasaraneni, Bhavani Prasad. "AI-Driven Approaches for Fraud Prevention in Health Insurance: Techniques, Models, and Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 136-180.
Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Techniques for Demand Forecasting in Retail Supply Chains: Models, Applications, and Real-World Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 180-218.
Kasaraneni, Ramana Kumar. "AI-Enhanced Portfolio Optimization: Balancing Risk and Return with Machine Learning Models." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 219-265.
Pattyam, Sandeep Pushyamitra. "AI-Driven Financial Market Analysis: Advanced Techniques for Stock Price Prediction, Risk Management, and Automated Trading." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 100-135.
Kuna, Siva Sarana. "The Impact of AI on Actuarial Science in the Insurance Industry." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 451-493.
Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Dynamic Pricing in Insurance: Advanced Techniques, Models, and Real-World Application." Hong Kong Journal of AI and Medicine 4.1 (2024): 258-297.