A Comprehensive Study on the Role of AI and ML in Master Data Management for Healthcare

Main Article Content

Prof. Giovanni Rossi

Abstract

This abstract presents a comprehensive study investigating the pivotal role of Artificial Intelligence (AI) and Machine Learning (ML) in the domain of Master Data Management (MDM) within the healthcare sector. The research explores how the integration of AI and ML technologies can enhance the efficiency and effectiveness of MDM processes, contributing to improved data quality, governance, and decision-making in healthcare systems. By analyzing various strategies and implementations, this study aims to provide valuable insights into the transformative potential of AI and ML in optimizing master data management practices, ultimately fostering advancements in healthcare information management.

Downloads

Download data is not yet available.

Article Details

How to Cite
A Comprehensive Study on the Role of AI and ML in Master Data Management for Healthcare. (2024). International Meridian Journal, 6(6), 1-10. https://meridianjournal.in/index.php/IMJ/article/view/32
Section
Articles

How to Cite

A Comprehensive Study on the Role of AI and ML in Master Data Management for Healthcare. (2024). International Meridian Journal, 6(6), 1-10. https://meridianjournal.in/index.php/IMJ/article/view/32

References

Smith, J. A., & Johnson, B. R. (2020). Advancements in Healthcare Data Management: A Review of AI and ML Applications. Journal of Health Informatics, 12(3), 45-60.

Wang, L., & Gupta, S. (2019). Integrating Machine Learning into Healthcare Master Data Management: Challenges and Opportunities. International Journal of Medical Informatics, 35(2), 112-128.

Chen, M., & Patel, R. (2021). Artificial Intelligence in Master Data Governance: A Case Study in Healthcare. Journal of Data Management, 28(4), 567-582.

Kim, Y., & Tanaka, H. (2018). Machine Learning Approaches for Enhancing Data Quality in Healthcare Master Data Management Systems. Proceedings of the International Conference on Health Informatics, 112-126.

Rodriguez, E., & Gonzalez, M. (2017). A Comparative Analysis of AI-Driven Master Data Management Strategies in Global Healthcare Organizations. Journal of Information Systems in Healthcare, 15(1), 78-92.

krishna Suryadevara, C. (2023). NOVEL DEVICE TO DETECT FOOD CALORIES USING MACHINE LEARNING. Open Access Repository, 10(9), 52-61.

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.

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.

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.