Unlocking the Potential of Healthcare Data: AI, ML, and Master Data Management Synergy
Abstract
The abstract explores the synergistic integration of Artificial Intelligence (AI), Machine Learning (ML), and Master Data Management (MDM) in unlocking the vast potential of healthcare data. This interdisciplinary approach aims to enhance data quality, governance, and decision-making processes within the healthcare ecosystem. By leveraging AI and ML algorithms, healthcare organizations can analyze massive datasets, derive valuable insights, and improve precision medicine initiatives. Additionally, MDM plays a crucial role in organizing and maintaining the integrity of healthcare data, ensuring a reliable foundation for AI and ML applications. This paper examines the challenges and opportunities associated with this synergy, providing a comprehensive analysis of strategies to optimize patient outcomes, transform healthcare systems, and pave the way for data-driven innovations in the field.
Downloads
References
Smith, J. A., & Johnson, R. B. (2020). Data Governance in Healthcare: A Comprehensive Overview. Journal of Health Informatics, 8(2), 112-130.
Chen, L., & Wang, Y. (2019). Machine Learning Applications in Healthcare: A Review. Health Information Science and Systems, 7(1), 1-14.
Brown, M., & Jones, A. (2018). Master Data Management in Healthcare: Best Practices and Challenges. Journal of Healthcare Information Management, 32(4), 27-35.
Gupta, S., & Jain, A. (2021). Artificial Intelligence in Precision Medicine: Current Trends and Future Directions. Frontiers in Genetics, 12, 647985.
Rodriguez, E., & Kim, S. (2019). Synergies of AI and Master Data Management in Healthcare: A Case Study Approach. Journal of Medical Systems, 43(12), 353.
krishna Suryadevara, C. (2023). NOVEL DEVICE TO DETECT FOOD CALORIES USING MACHINE LEARNING. Open Access Repository, 10(9), 52-61.
Atluri, H., & Thummisetti, B. S. P. (2023). Optimizing Revenue Cycle Management in Healthcare: A Comprehensive Analysis of the Charge Navigator System. International Numeric Journal of Machine Learning and Robots, 7(7), 1-13.
Kasula, B. Y. (2024). Ethical Implications and Future Prospects of Artificial Intelligence in Healthcare: A Research Synthesis. International Meridian Journal, 6(6), 1-7.
Kasula, B. Y. (2024). Optimizing Healthcare Delivery: Machine Learning Applications and Innovations for Enhanced Patient Outcomes. International Journal of Creative Research In Computer Technology and Design, 6(6), 1-7.
Pansara, R. (2023). Digital Disruption in Transforming AgTech Business Models for a Sustainable Future. Transactions on Latest Trends in IoT, 6(6), 67-76.
Atluri, H., & Thummisetti, B. S. P. (2022). A Holistic Examination of Patient Outcomes, Healthcare Accessibility, and Technological Integration in Remote Healthcare Delivery. Transactions on Latest Trends in Health Sector, 14(14).
Kasula, B. Y. (2023). Machine Learning Applications in Diabetic Healthcare: A Comprehensive Analysis and Predictive Modeling. International Numeric Journal of Machine Learning and Robots, 7(7).
Kasula, B. Y. (2023). The Role of Blockchain Technology in Securing Electronic Health Records. Transactions on Latest Trends in Artificial Intelligence, 4(4).
Pansara, R. (2023). MDM Governance Framework in the Agtech & Manufacturing Industry. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.
Kasula, B. Y. (2023). Leveraging Natural Language Processing and Machine Learning for Enhanced Content Rating. International Meridian Journal, 5(5).
Kasula, B. Y. (2023). Exploring the Impact of Telemedicine on Patient Engagement and Healthcare Accessibility. International Transactions in Machine Learning, 5(5), 1-7.
Pansara, R. (2023). From fields to factories a technological odyssey in agtech and manufacturing. International Journal of Managment Education for Sustainable Development, 6(6), 1-12.
Kasula, B. Y. (2023). Ethical Considerations in the Adoption of Artificial Intelligence for Mental Health Diagnosis. International Journal of Creative Research In Computer Technology and Design, 5(5), 1-7.
Pansara, R. (2023). Navigating Data Management in the Cloud-Exploring Limitations and Opportunities. Transactions on Latest Trends in IoT, 6(6), 57-66.
Kasula, B. Y. (2022). Assessing the Effectiveness of Wearable Health Devices in Promoting Lifestyle Changes. International Meridian Journal, 4(4), 1-7.
Kasula, B. Y. (2022). Machine Learning Applications for Early Detection and Intervention in Chronic Diseases. International Transactions in Artificial Intelligence, 6(6), 1-7.
Kasula, B. Y. (2020). Fraud Detection and Prevention in Blockchain Systems Using Machine Learning. International Meridian Journal, 2(2), 1-8.
Pansara, R. (2023). Review & Analysis of Master Data Management in Agtech & Manufacturing industry. International Journal of Sustainable Development in Computing Science, 5(3), 51-59.
Kasula, B. Y. K. (2020). Optimizing Smart Contracts with Machine Learning Techniques in Blockchain. International Journal of Creative Research In Computer Technology and Design, 2(2).
Pansara, R. (2021). “MASTER DATA MANAGEMENT IMPORTANCE IN TODAY’S ORGANIZATION. International Journal of Management (IJM), 12(10).
Kasula, B. Y. (2020). Digital Inclusion in Smart Cities: Bridging the Healthcare Gap through IoT Technologies. International Journal of Sustainable Devlopment in field of IT, 12(12), 1-7.
Pansara, R. (2021). “MASTER DATA MANAGEMENT IMPORTANCE IN TODAY’S ORGANIZATION. International Journal of Management (IJM), 12(10).
Kasula, B. Y. (2019). Enhancing Classification Precision: Exploring the Power of Support-Vector Networks in Machine Learning. International Scientific Journal for Research, 1(1).
Pansara, R. (2023). Cultivating Data Quality to Strategies, Challenges, and Impact on Decision-Making. International Journal of Managment Education for Sustainable Development, 6(6), 24-33.
Kasula, B. Y. (2017). The Role of Edge Computing in Real-Time Analytics for Smart City Healthcare Applications. Transaction on Recent Developments in Industrial IoT, 9(9), 1-7.
Pansara, R. (2023). Unraveling the Complexities of Data Governance with Strategies, Challenges, and Future Directions. Transactions on Latest Trends in IoT, 6(6), 46-56.
Kasula, B. Y. (2017). Machine Learning Unleashed: Innovations, Applications, and Impact Across Industries. International Transactions in Artificial Intelligence, 1(1), 1-7.
Kasula, B. Y. (2024). Advancements in AI-driven Healthcare: A Comprehensive Review of Diagnostics, Treatment, and Patient Care Integration. International Journal of Machine Learning for Sustainable Development, 1(1), 1-5.
Thummisetti, B. S. P., & Atluri, H. (2024). Advancing Healthcare Informatics for Empowering Privacy and Security through Federated Learning Paradigms. International Journal of Sustainable Development in Computing Science, 1(1), 1-16.
Singh, K. Artificial Intelligence & Cloud in Healthcare: Analyzing Challenges and Solutions Within Regulatory Boundaries.
Bhanushali, A., Singh, K., Sivagnanam, K., & Patel, K. K. (2023). WOMEN'S BREAST CANCER PREDICTED USING THE RANDOM FOREST APPROACH AND COMPARISON WITH OTHER METHODS. Journal of Data Acquisition and Processing, 38(4), 921.
Singh, K. HEALTHCARE FRAUDULENCE: LEVERAGING ADVANCED ARTIFICIAL INTELLIGENCE TECHNIQUES FOR DETECTION.
Pansara, R. (2023). Seeding the Future by Exploring Innovation and Absorptive Capacity in Agriculture 4.0 and Agtechs. International Journal of Sustainable Development in Computing Science, 5(2), 46-59.
Atluri, H., & Thummisetti, B. S. P. (2024). ENHANCING ANTIBIOTIC PRESCRIBING IN URGENT CARE BY LEVERAGING LARGE LANGUAGE MODELS FOR OPTIMIZED CLINICAL DECISION SUPPORT.
