Blockchain-Enhanced Machine Learning for Predictive Analytics in Precision Medicine
Keywords:
Blockchain, Machine Learning, Predictive Analytics, Precision Medicine, Data Security, Healthcare Interoperability, Smart ContractsAbstract
This research integrates Blockchain and machine learning (ML) for precision medicine predictive analytics to solve data privacy, security, interoperability, and trust issues. Secondary data from peer-reviewed publications, case studies, and technical reports are reviewed to examine blockchain-enhanced ML's potential and limits in healthcare. Researchers found that Blockchain increases data integrity, secure data sharing, and ML model transparency, boosting healthcare stakeholder trust and cooperation. Privacy rules like GDPR and HIPAA are met while the connection allows individualized treatment recommendations, early illness identification, and enhanced clinical trials. According to the report, scalability, legacy system integration, and regulatory difficulties hinder adoption. Policy implications emphasize the need for clear legislative frameworks that balance innovation and privacy and promote stakeholder engagement to address these challenges. This research sheds light on how Blockchain and ML may be used synergistically to enhance precision medicine and provide more secure, transparent, and effective healthcare solutions.
References
Addimulam, S., Rahman, K., Karanam, R. K., & Natakam, V. M. (2021). AI-Powered Diagnostics: Revolutionizing Medical Research and Patient Care. Technology & Management Review, 6, 36-49. https://upright.pub/index.php/tmr/article/view/155
Ahmmed, S., Narsina, D., Addimulam, S., & Boinapalli, N. R. (2021). AI-Powered Financial Engineering: Optimizing Risk Management and Investment Strategies. Asian Accounting and Auditing Advancement, 12(1), 37–45. https://4ajournal.com/article/view/96
Alonso, S. G., de la Torre, D. I., Zapiraín, B. G. (2019). Predictive, Personalized, Preventive and Participatory (4P) Medicine Applied to Telemedicine and eHealth in the Literature. Journal of Medical Systems, 43(5), 1-10. https://doi.org/10.1007/s10916-019-1279-4
Asadullah, A., Rahman, K., Azad, M. M. (2021). Accurate and Predictable Cardiovascular Disease Detection by Machine Learning. Journal of Cardiovascular Disease Research, 12(3), 448-454.
Berghe, T. V., Hoste, E. (2019). Paving the Way for Precision Medicine v2.0 in Intensive Care by Profiling Necroinflammation in Biofluids. Cell Death and Differentiation, 26(1), 83-98. https://doi.org/10.1038/s41418-018-0196-2
Bublitz, F. M., Oetomo, A., Sahu, K. S., Kuang, A., Fadrique, L. X. (2019). Disruptive Technologies for Environment and Health Research: An Overview of Artificial Intelligence, Blockchain, and Internet of Things. International Journal of Environmental Research and Public Health, 16(20). https://doi.org/10.3390/ijerph16203847
Devarapu, K., Rahman, K., Kamisetty, A., & Narsina, D. (2019). MLOps-Driven Solutions for Real-Time Monitoring of Obesity and Its Impact on Heart Disease Risk: Enhancing Predictive Accuracy in Healthcare. International Journal of Reciprocal Symmetry and Theoretical Physics, 6, 43-55. https://upright.pub/index.php/ijrstp/article/view/160
Gade, P. K. (2019). MLOps Pipelines for GenAI in Renewable Energy: Enhancing Environmental Efficiency and Innovation. Asia Pacific Journal of Energy and Environment, 6(2), 113-122. https://doi.org/10.18034/apjee.v6i2.776
Gade, P. K., Sridharlakshmi, N. R. B., Allam, A. R., & Koehler, S. (2021). Machine Learning-Enhanced Beamforming with Smart Antennas in Wireless Networks. ABC Journal of Advanced Research, 10(2), 207-220. https://doi.org/10.18034/abcjar.v10i2.770
Goda, D. R. (2020). Decentralized Financial Portfolio Management System Using Blockchain Technology. Asian Accounting and Auditing Advancement, 11(1), 87–100. https://4ajournal.com/article/view/87
Gummadi, J. C. S., Narsina, D., Karanam, R. K., Kamisetty, A., Talla, R. R., & Rodriguez, M. (2020). Corporate Governance in the Age of Artificial Intelligence: Balancing Innovation with Ethical Responsibility. Technology & Management Review, 5, 66-79. https://upright.pub/index.php/tmr/article/view/157
Gummadi, J. C. S., Thompson, C. R., Boinapalli, N. R., Talla, R. R., & Narsina, D. (2021). Robotics and Algorithmic Trading: A New Era in Stock Market Trend Analysis. Global Disclosure of Economics and Business, 10(2), 129-140. https://doi.org/10.18034/gdeb.v10i2.769
Kamel Boulos, M. N., Peng, G., VoPham, T. (2019). An Overview of GeoAI Applications in Health and Healthcare. International Journal of Health Geographics, 18. https://doi.org/10.1186/s12942-019-0171-2
Kamisetty, A., Onteddu, A. R., Kundavaram, R. R., Gummadi, J. C. S., Kothapalli, S., Nizamuddin, M. (2021). Deep Learning for Fraud Detection in Bitcoin Transactions: An Artificial Intelligence-Based Strategy. NEXG AI Review of America, 2(1), 32-46.
Karanam, R. K., Natakam, V. M., Boinapalli, N. R., Sridharlakshmi, N. R. B., Allam, A. R., Gade, P. K., Venkata, S. G. N., Kommineni, H. P., & Manikyala, A. (2018). Neural Networks in Algorithmic Trading for Financial Markets. Asian Accounting and Auditing Advancement, 9(1), 115–126. https://4ajournal.com/article/view/95
Khezr, S., Moniruzzaman, M., Yassine, A., Benlamri, R. (2019). Blockchain Technology in Healthcare: A Comprehensive Review and Directions for Future Research. Applied Sciences, 9(9). https://doi.org/10.3390/app9091736
Kommineni, H. P. (2019). Cognitive Edge Computing: Machine Learning Strategies for IoT Data Management. Asian Journal of Applied Science and Engineering, 8(1), 97-108. https://doi.org/10.18034/ajase.v8i1.123
Kommineni, H. P. (2020). Automating SAP GTS Compliance through AI-Powered Reciprocal Symmetry Models. International Journal of Reciprocal Symmetry and Theoretical Physics, 7, 44-56. https://upright.pub/index.php/ijrstp/article/view/162
Kommineni, H. P., Fadziso, T., Gade, P. K., Venkata, S. S. M. G. N., & Manikyala, A. (2020). Quantifying Cybersecurity Investment Returns Using Risk Management Indicators. Asian Accounting and Auditing Advancement, 11(1), 117–128. https://4ajournal.com/article/view/97
Kothapalli, S. (2021). Blockchain Solutions for Data Privacy in HRM: Addressing Security Challenges. Journal of Fareast International University, 4(1), 17-25. https://jfiu.weebly.com/uploads/1/4/9/0/149099275/2021_3.pdf
Kothapalli, S., Manikyala, A., Kommineni, H. P., Venkata, S. G. N., Gade, P. K., Allam, A. R., Sridharlakshmi, N. R. B., Boinapalli, N. R., Onteddu, A. R., & Kundavaram, R. R. (2019). Code Refactoring Strategies for DevOps: Improving Software Maintainability and Scalability. ABC Research Alert, 7(3), 193–204. https://doi.org/10.18034/ra.v7i3.663
Kundavaram, R. R., Rahman, K., Devarapu, K., Narsina, D., Kamisetty, A., Gummadi, J. C. S., Talla, R. R., Onteddu, A. R., & Kothapalli, S. (2018). Predictive Analytics and Generative AI for Optimizing Cervical and Breast Cancer Outcomes: A Data-Centric Approach. ABC Research Alert, 6(3), 214-223. https://doi.org/10.18034/ra.v6i3.672
Mallipeddi, S. R. (2022). Harnessing AI and IoT Technologies for Sustainable Business Operations in the Energy Sector. Asia Pacific Journal of Energy and Environment, 9(1), 37-48. https://doi.org/10.18034/apjee.v9i1.735
Narsina, D., Gummadi, J. C. S., Venkata, S. S. M. G. N., Manikyala, A., Kothapalli, S., Devarapu, K., Rodriguez, M., & Talla, R. R. (2019). AI-Driven Database Systems in FinTech: Enhancing Fraud Detection and Transaction Efficiency. Asian Accounting and Auditing Advancement, 10(1), 81–92. https://4ajournal.com/article/view/98
Onteddu, A. R., Venkata, S. S. M. G. N., Ying, D., & Kundavaram, R. R. (2020). Integrating Blockchain Technology in FinTech Database Systems: A Security and Performance Analysis. Asian Accounting and Auditing Advancement, 11(1), 129–142. https://4ajournal.com/article/view/99
Rahman, K. (2017). Digital Platforms in Learning and Assessment: The Coming of Age of Artificial Intelligence in Medical Checkup. International Journal of Reciprocal Symmetry and Theoretical Physics, 4, 1-5. https://upright.pub/index.php/ijrstp/article/view/3
Rahman, K. (2021). Biomarkers and Bioactivity in Drug Discovery using a Joint Modelling Approach. Malaysian Journal of Medical and Biological Research, 8(2), 63-68. https://doi.org/10.18034/mjmbr.v8i2.585
Richardson, N., Manikyala, A., Gade, P. K., Venkata, S. S. M. G. N., Asadullah, A. B. M., & Kommineni, H. P. (2021). Emergency Response Planning: Leveraging Machine Learning for Real-Time Decision-Making. Technology & Management Review, 6, 50-62. https://upright.pub/index.php/tmr/article/view/163
Roberts, C., Kundavaram, R. R., Onteddu, A. R., Kothapalli, S., Tuli, F. A., Miah, M. S. (2020). Chatbots and Virtual Assistants in HRM: Exploring Their Role in Employee Engagement and Support. NEXG AI Review of America, 1(1), 16-31.
Rodriguez, M., Sridharlakshmi, N. R. B., Boinapalli, N. R., Allam, A. R., & Devarapu, K. (2020). Applying Convolutional Neural Networks for IoT Image Recognition. International Journal of Reciprocal Symmetry and Theoretical Physics, 7, 32-43. https://upright.pub/index.php/ijrstp/article/view/158
Rogers, M. A., Aikawa, E. (2019). Cardiovascular Calcification: Artificial Intelligence and Big Data Accelerate Mechanistic Discovery. Nature Reviews. Cardiology, 16(5), 261-274. https://doi.org/10.1038/s41569-018-0123-8
Shuaib, K., Saleous, H., Shuaib, K., Zaki, N. (2019). Blockchains for Secure Digitized Medicine. Journal of Personalized Medicine, 9(3), 35. https://doi.org/10.3390/jpm9030035
Siyal, A. A., Junejo, A. Z., Zawish, M., Ahmed, K., Khalil, A. (2019). Applications of Blockchain Technology in Medicine and Healthcare: Challenges and Future Perspectives. Cryptography, 3(1), 3. https://doi.org/10.3390/cryptography3010003
Sridharlakshmi, N. R. B. (2020). The Impact of Machine Learning on Multilingual Communication and Translation Automation. NEXG AI Review of America, 1(1), 85-100.
Sridharlakshmi, N. R. B. (2021). Data Analytics for Energy-Efficient Code Refactoring in Large-Scale Distributed Systems. Asia Pacific Journal of Energy and Environment, 8(2), 89-98. https://doi.org/10.18034/apjee.v8i2.771
Talla, R. R., Manikyala, A., Gade, P. K., Kommineni, H. P., & Deming, C. (2022). Leveraging AI in SAP GTS for Enhanced Trade Compliance and Reciprocal Symmetry Analysis. International Journal of Reciprocal Symmetry and Theoretical Physics, 9, 10-23. https://upright.pub/index.php/ijrstp/article/view/164
Talla, R. R., Manikyala, A., Nizamuddin, M., Kommineni, H. P., Kothapalli, S., Kamisetty, A. (2021). Intelligent Threat Identification System: Implementing Multi-Layer Security Networks in Cloud Environments. NEXG AI Review of America, 2(1), 17-31.
Thompson, C. R., Talla, R. R., Gummadi, J. C. S., Kamisetty, A (2019). Reinforcement Learning Techniques for Autonomous Robotics. Asian Journal of Applied Science and Engineering, 8(1), 85-96. https://ajase.net/article/view/94
Venkata, S. S. M. G. N., Gade, P. K., Kommineni, H. P., Manikyala, A., & Boinapalli , N. R. (2022). Bridging UX and Robotics: Designing Intuitive Robotic Interfaces. Digitalization & Sustainability Review, 2(1), 43-56. https://upright.pub/index.php/dsr/article/view/159
Winter, J. S., Davidson, E. (2019). Governance of Artificial Intelligence and Personal Health Information. Digital Policy, Regulation and Governance, 21(3), 280-290. https://doi.org/10.1108/DPRG-08-2018-0048
Yang, J., Hassan, M. M. O., Nam-Yong, L., Mohiuddin, A., Chul-Soo, K. (2019). Proof-of-Familiarity: A Privacy-Preserved Blockchain Scheme for Collaborative Medical Decision-Making. Applied Sciences, 9(7). https://doi.org/10.3390/app9071370
Downloads
Published
Issue
Section
License
Copyright (c) 2022 American Observer PressThis journal operates under a hybrid access model. Published articles may be available through paid access or subscription, while selected articles may be published as Open Access upon payment of an Open Access fee.
For non-Open Access articles, all rights are reserved by the publisher. Open Access articles, when applicable, are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License, which permits sharing and adaptation for non-commercial purposes, provided appropriate credit is given to the original work.
