| 书目名称 | Machine Learning for Health Informatics |
| 副标题 | State-of-the-Art and |
| 编辑 | Andreas Holzinger |
| 视频video | |
| 概述 | Hot topics in machine learning for health informatics.State-of-the-art survey and output of the international HCI-KDD expert network.Discusses open problems and future challenges in order to stimulate |
| 丛书名称 | Lecture Notes in Computer Science |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2016 |
| 关键词 | algorithms; artificial intelligence; big data; classification; data mining; data science; decision support |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-50478-0 |
| isbn_softcover | 978-3-319-50477-3 |
| isbn_ebook | 978-3-319-50478-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 |
| issn_series | 0302-9743 |
| copyright | Springer International Publishing AG 2016 |
发表于 2025-3-21 16:05:13
