AI-Driven Healthcare Transformation: Exploring the Impact of Machine Learning Algorithms on Diagnosis and Treatment
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Abstract
This research paper investigates the transformative influence of artificial intelligence (AI) in the healthcare domain, with a specific focus on the impact of machine learning algorithms on diagnosis and treatment. As the healthcare industry embraces advanced technologies, the integration of machine learning stands out as a pivotal force reshaping traditional practices.
The abstract begins by acknowledging the overarching theme of AI-driven healthcare transformation and narrows the scope to delve into the specific realm of machine learning algorithms. These algorithms, capable of processing vast datasets and recognizing intricate patterns, hold immense potential for enhancing diagnostic accuracy and treatment efficacy.
The study critically examines the implications of machine learning in diagnosis, exploring how these algorithms contribute to early detection, precision, and personalized medicine. Additionally, it investigates their role in treatment strategies, considering optimization, individualization, and adaptability to evolving medical scenarios.
The abstract emphasizes the significance of this research in the context of advancing healthcare practices. It outlines the methodology, incorporating literature reviews, case studies, and data analyses to provide a comprehensive understanding of the current landscape and future possibilities. Through this, the paper aims to contribute valuable insights that can inform healthcare professionals, researchers, and policymakers about the evolving role of machine learning in reshaping diagnosis and treatment paradigms within the healthcare sector.
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Kasula, B. Y. (2020). Reinforcement Learning Applications for Security Enhancement in Smart Contracts. (2020). International Journal of Machine Learning and Artificial Intelligence, 1(1), 1-8. https://jmlai.in/index.php/ijmlai/article/view/14
Whig, P (2023 ) Data Quality Assurance in the Age of Big Data: Strategies and Best Practices for Reliable Data Management. (2023). International Meridian Journal, 5(5). https://meridianjournal.in/index.php/IMJ/article/view/17
Whig, P., Kouser, S., Khan, T. A., Mehdi, S. A., Alam, N., & Nadikattu, R. R. (2023). Gender Differences in Diabetes Care and Management Using AI. In Combating Women's Health Issues with Machine Learning (pp. 74-95). CRC Press.
WHIG, P. (2023). Empowering Sustainable Development through Big Data. International Journal of Sustainable Development in Computing Science, 5(3), 1-10. Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/321
WHIG, P. (2023). Leveraging the Internet of Things (IoT): Innovations, Challenges, and Future Prospects. International Journal of Sustainable Devlopment in Field of IT, 15(15). Retrieved from https://journals.threws.com/index.php/IT/article/view/187
Whig, D. P., Ganesan, V., & Venkata, S. (2023). Combatting Falsehoods and Discriminatory Speech with NLP and ML Techniques. International Transactions in Machine Learning, 5(5). Retrieved from https://isjr.co.in/index.php/ITML/article/view/131
Kasula, B. Y. (2020). Fraud Detection and Prevention in Blockchain Systems Using Machine Learning. (2020). International Meridian Journal, 2(2), 1-8. https://meridianjournal.in/index.php/IMJ/article/view/22
Kasula, B. Y. (2021). Ethical and Regulatory Considerations in AI-Driven Healthcare Solutions. (2021). International Meridian Journal, 3(3), 1-8. https://meridianjournal.in/index.php/IMJ/article/view/23
Kasula, B. Y. (2021). AI-Driven Innovations in Healthcare: Improving Diagnostics and Patient Care. (2021). International Journal of Machine Learning and Artificial Intelligence, 2(2), 1-8. https://jmlai.in/index.php/ijmlai/article/view/15
Pansara, R. (2023). Navigating Data Management in the Cloud-Exploring Limitations and Opportunities. Transactions on Latest Trends in IoT, 6(6), 57-66.
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.
Pansara, R. (2023). MDM Governance Framework in the Agtech & Manufacturing Industry. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.
Pansara, R. (2023). Digital Disruption in Transforming AgTech Business Models for a Sustainable Future. Transactions on Latest Trends in IoT, 6(6), 67-76.
Kasula, B. Y. (2021). Machine Learning in Healthcare: Revolutionizing Disease Diagnosis and Treatment. (2021). International Journal of Creative Research In Computer Technology and Design, 3(3). https://jrctd.in/index.php/IJRCTD/article/view/27
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. (2022). Harnessing Machine Learning Algorithms for Personalized Cancer Diagnosis and Prognosis. International Journal of Sustainable Development in Computing Science, 4(1), 1-8. Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/412
Kasula, B. (2022). Automated Disease Classification in Dermatology: Leveraging Deep Learning for Skin Disorder Recognition. International Journal of Sustainable Development in Computing Science, 4(4), 1-8. Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/414
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.