Fog Computing for Intelligent Cloud IoT Systems

7A Complete Study on Machine Learning Algorithms for Medical Data Analysis

Inderdeep Kaur* and Aleem Ali

Department of Computer Science and Engineering, Chandigarh University, Gharuan, Mohali, Punjab, India

Abstract

Machine learning (ML) algorithms have become increasingly important in healthcare because of their ability to analyze vast amounts of data from various patients and provide insights that can improve patient outcomes, reduce costs, and enhance overall efficiency. These algorithms may help in disease diagnosis, treatment optimization, prediction of treatment outcomes, and patient risk assessment. They can also assist in clinical decision making, resource allocation, and disease surveillance. Machine learning algorithms have been shown to be invaluable in the fight against COVID-19 in healthcare settings. These algorithms have been used in various ways, such as in developing models that accurately detect COVID-19 from medical images, predicting disease progression, and assisting with drug development. This chapter describes the current state-of-the-art machine learning algorithms used in medical data analysis, including supervised, unsupervised, and reinforcement learning. We also discuss the challenges in medical data analysis, such as the data quality, privacy concerns, and interpretability of ML algorithms. Finally, we highlight the potential of different machine-learning algorithms. Ultimately, the purpose of this chapter is to serve as a resource for academic ...