Machine Learning for Health Informatics is popular PDF and ePub book, written by Andreas Holzinger in 2016-12-09, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Machine Learning for Health Informatics can be Read Online from any device for your convenience.
Machine Learning for Health Informatics Book PDF Summary
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
Detail Book of Machine Learning for Health Informatics PDF
- Author : Andreas Holzinger
- Release : 09 December 2016
- Publisher : Springer
- ISBN : 9783319504780
- Genre : Computers
- Total Page : 481 pages
- Language : English
- PDF File Size : 12,8 Mb
If you're still pondering over how to secure a PDF or EPUB version of the book Machine Learning for Health Informatics by Andreas Holzinger, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.
