Machine Learning for Healthcare Analytics Projects

aria-expanded"true" class"a-expander-content a-expander-partial-collapse-content a-expander-content-expanded" style'box-sizing: border-box; overflow: hidden; position: relative; color: rgb(15, 17, 17); font-family: "Amazon Ember", Arial, sans-serif; font-size: 14px; padding-bottom: 20px;' style"box-sizing: border-box; padding: 0px 0px 4px; margin: 0px; text-rendering: optimizelegibility; font-weight: 700; font-size: 18px; line-height: 24px;"Book Description "box-sizing: border-box; padding: 0px; margin: 0px 0px 14px;"Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. "box-sizing: border-box; padding: 0px; margin: -4px 0px 14px;"This book will teach you how to implement key machine learning algorithms and walk you through their use cases employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors (KNN) models. In the final chapters, you will create a deep neural network in Keras to predict the onset of diabetes in a huge dataset of patients. You will also learn how to predict heart diseases using neural networks. "box-sizing: border-box; padding: 0px; margin: -4px 0px 14px;" the end of this book, you will have learned how to address long-standing challenges, provide specialized solutions for how to deal with them, and carry out a range of cognitive tasks in the healthcare domain. style'box-sizing: border-box; padding: 0px 0px 4px; margin: 0px; text-rendering: optimizelegibility; font-weight: 700; font-size: 18px; line-height: 24px; color: rgb(15, 17, 17); font-family: "Amazon Ember", Arial, sans-serif;'Key Features