Practical AI for Healthcare Professionals: Machine Learning with Numpy, Scikit-learn, and TensorFlow

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Abstract

Artificial Intelligence (AI) is a buzzword in the healthcare sphere today. However, notions of what AI actually is and how it works are often not discussed. Furthermore, information on AI implementation is often tailored towards seasoned programmers rather than the healthcare professional/beginner coder. This book gives an introduction to practical AI in the medical sphere, focusing on real-life clinical problems, how to solve them with actual code, and how to evaluate the efficacy of those solutions. You'll start by learning how to diagnose problems as ones that can and cannot be solved with AI. You'll then learn the basics of computer science algorithms, neural networks, and when each should be applied. Then you'll tackle the essential parts of basic Python programming relevant to data processing and making AI programs. The Tensorflow/Keras library along with Numpy and Scikit-Learn are covered as well.

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Suri, A. (2021). Practical AI for Healthcare Professionals: Machine Learning with Numpy, Scikit-learn, and TensorFlow. Practical AI for Healthcare Professionals: Machine Learning with Numpy, Scikit-learn, and TensorFlow (pp. 1–254). Apress Media LLC. https://doi.org/10.1007/978-1-4842-7780-5

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