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Can I read AI for Healthcare with Keras and Tensorflow 2.0 : Design, Develop, and Deploy Machine Learning Models Using Healthcare Data on EtoBox?

AI for Healthcare with Keras and Tensorflow 2.0 : Design, Develop, and Deploy Machine Learning Models Using Healthcare Data by Anshik Bansal is a nonfiction available to read on EtoBox.

What is AI for Healthcare with Keras and Tensorflow 2.0 : Design, Develop, and Deploy Machine Learning Models Using Healthcare Data about?

Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries. This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-populations using a multi-task setup when you are working on any downstream task. You also will try to predict ICD-9 codes using the same data. You will study transformer models. And you will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. You will look at semi-supervised approaches that are used in a low training data setting, a case very often observed in specialized domains such as healthcare. You will be introduced to applications of advanced topics such as the graph convolutional network and how you can develop and optimize image analysis pipelines when using 2D and 3D medical images. The concluding section shows you how to build and design a closed-domain Q&A system with paraphrasing, re-ranking, an

Who reads AI for Healthcare with Keras and Tensorflow 2.0 : Design, Develop, and Deploy Machine Learning Models Using Healthcare Data?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Anshik Bansal
Publisher
Apress L. P.
Published
2021
Language
EN
ISBN
9781484270875
Category
nonfiction
Subjects
Computer Science, Language Learning, Medical

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