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.
Andreas Holzinger
Machine Learning for Health Informatics [PDF ebook]
State-of-the-Art and Future Challenges
Machine Learning for Health Informatics [PDF ebook]
State-of-the-Art and Future Challenges
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Ngôn ngữ Anh ● định dạng PDF ● ISBN 9783319504780 ● Biên tập viên Andreas Holzinger ● Nhà xuất bản Springer International Publishing ● Được phát hành 2016 ● Có thể tải xuống 3 lần ● Tiền tệ EUR ● TÔI 6646888 ● Sao chép bảo vệ Adobe DRM
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