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

This book provides 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. It covers basic computer science and programming concepts, machine learning algorithms, and deep learning for medical diagnostics. Physicians and other healthcare professionals who can master these skills will be able to lead AI-based research and diagnostic tool development, benefiting countless patients.

Format: Paperback / softback
Length: 254 pages
Publication date: 14 December 2021
Publisher: APress

Artificial Intelligence (AI) is a hot topic in the healthcare industry, but misconceptions about what AI is and how it works are common. Furthermore, information on AI implementation is often geared towards experienced programmers rather than healthcare professionals or beginner coders. This book provides an introduction to practical AI in the medical field, focusing on real-life clinical problems, how to solve them with actual code, and how to evaluate the effectiveness of those solutions.

You will begin by learning how to identify problems that can and cannot be solved with AI. You will then learn the basics of computer science algorithms, neural networks, and when each should be applied. You will then tackle the essential parts of basic Python programming relevant to data processing and creating AI programs. The TensorFlow/Keras library, along with Numpy and Scikit-Learn, will also be covered.

Once you have mastered these basic computer science and programming concepts, you can dive into projects with code, implementation details, and explanations. These projects give you the opportunity to explore using machine learning algorithms for issues such as predicting the probability of hospital admission from emergency room triage and patient demographic data. We will then use deep learning to determine whether patients have pneumonia using chest X-ray images.

The topics covered in this book not only encompass areas of the medical field where AI is already playing a major role, but are also designed to cover as much of AI that is relevant to medical diagnostics as possible. Along the way, readers can expect to learn data processing, how to conceptualize problems that can be solved by AI, and how to program solutions.

Weight: 426g
Dimension: 155 x 234 x 23 (mm)
ISBN-13: 9781484277799
Edition number: 1st ed.