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Advancing Healthcare Outcomes Through Machine Learning Innovations
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Author(s): Sudheer Kumar Kothuru (Bausch Health Companies, USA), Ramesh Chandra Aditya Komperla (Geico, USA), M. Kadar Shah (Dhaanish Ahmed College of Engineering, India), Vasanthakumari Sundararajan (Wollega University, Ethiopia), P. Paramasivan (Dhaanish Ahmed College of Engineering, India)and R. Regin (SRM Instıtute of Science and Technology, India)
Copyright: 2024
Pages: 17
Source title:
Cross-Industry AI Applications
Source Author(s)/Editor(s): P. Paramasivan (Dhaanish Ahmed College of Engineering, India), S. Suman Rajest (Dhaanish Ahmed College of Engineering, India), Karthikeyan Chinnusamy (Veritas, USA), R. Regin (SRM Instıtute of Science and Technology, India)and Ferdin Joe John Joseph (Thai-Nichi Institute of Technology, Thailand)
DOI: 10.4018/979-8-3693-5951-8.ch015
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Abstract
This research chapter explores the transformative impact of machine learning (ML) in enhancing healthcare outcomes. With the rapid growth in healthcare data and the complexity of healthcare challenges, traditional analytical methods have become inadequate. Machine learning offers innovative solutions for diagnosing diseases, predicting patient outcomes, and personalizing patient care. This chapter reviews the literature on ML applications in healthcare, covering various methodologies and highlighting successful case studies. The research employs a comprehensive methodology, including data collection, model development, and rigorous testing, to investigate the effectiveness of ML algorithms in healthcare settings. The results demonstrate significant improvements in diagnostic accuracy, treatment personalization, and predictive analytics, evidenced through quantitative data presented in graphs and tables.
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