| 書目名稱 | Fundamentals of Machine Learning and Deep Learning in Medicine |
| 編輯 | Reza Borhani,Soheila Borhani,Aggelos K. Katsaggelo |
| 視頻video | http://file.papertrans.cn/351/350367/350367.mp4 |
| 概述 | Offers an accessible introduction to deep learning in medicine.Covers artificial intelligence topics with a focus on application and visualization.Includes over 100 end of chapter exercises |
| 圖書封面 |  |
| 描述 | .This book provides an accessible introduction to the foundations of machine learning and deep learning in medicine for medical students, researchers, and professionals who are not necessarily initiated in advanced mathematics but yearn for a better understanding of this disruptive technology and its impact on medicine. Once an esoteric subject known to few outside of computer science and engineering departments, today artificial intelligence (AI) is a widely popular technology used by scholars from all across the academic universe. In particular, recent years have seen a great deal of interest in the AI subfields of machine learning and deep learning from researchers in medicine and life sciences, evidenced by the rapid growth in the number of articles published on the topic in peer-reviewed medical journals over the last decade. The demand for high-quality educational resources in this area has never been greater than it is today, and will only continue to grow at a rapid pace...Expert authors remove the veil of unnecessary complexity that often surrounds machine learning and deep learning by employing a narrative style that emphasizes intuition in place of abstract mathematical |
| 出版日期 | Textbook 2022 |
| 關(guān)鍵詞 | Deep Learning; Internal Medicine; General Medicine; Machine Learning; Artificial Intelligence; Medical Da |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-19502-0 |
| isbn_softcover | 978-3-031-19501-3 |
| isbn_ebook | 978-3-031-19502-0 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機版|小黑屋|
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