Requirements: .PDF reader, 19.4 MB
Overview: In this book, we embark on a journey into the realm of predictive data modeling for biomedical data and imaging in healthcare. It explores the potential of predictive analytics in the field of medical science through utilizing various tools and techniques to unravel insights and enhance patient care. This volume creates a medium for an interchange of knowledge from expertise and concerns in the field of predictive data modeling. In detail, the research work on this will include the effective use of predictive data modeling algorithms to run image analysis tasks for understanding. Predictive Data Modelling for Biomedical Data and Imaging is divided into three sections, namely Section I – Beginning of Predictive Data Modeling for Biomedical Data and Imaging/Healthcare, Section II – Data Design and Analysis for Biomedical Data and Imaging/Healthcare, and Section III – Case Studies of Predictive Analytics for Biomedical Data and Imaging/Healthcare. We hope this book will inspire further research and innovation in the field of predictive data modeling for biomedical data and imaging in healthcare. Better healthcare and precise medicine may be developed using AI and multipurpose ML systems. These platforms may be used to find the best routes to customize and affordable therapies. Deep Learning algorithms focus on inducement of alike conclusions as human beings ensure by incessantly examining data conferring to a specified rational structure. TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks. TensorFlow is designed to be a flexible, scalable, and efficient platform for building and training Machine Learning models. Keras is an open-source neural network library written in Python.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://ouo.io/Ylbmwb
https://katfile.com/qx634osz1kwe/Predic … a.pdf.html.
