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Advances of Machine Learning for Knowledge Mining in Electronic Health Records
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Advances of Machine Learning for Knowledge Mining in Electronic Health Records
The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR, consisting of demographics, medical history, and diagnosis.
304 pages, 37 Tables, black and white; 121 Line drawings, black and white; 8 Halftones, black and wh
| Mediji | Grāmatas Hardcover Book (Grāmata ar cieto muguriņu un vāku) |
| Izlaists | 2025. gada 6. marts |
| ISBN13 | 9781032526102 |
| Izdevēji | Taylor & Francis Ltd |
| Lapas | 270 |
| Izmēri | 150 × 220 × 20 mm · 690 g |
| Valoda | Angļu |
| Redaktors | Fathimal, P. Mohamed (Government Polytechnic College, India) |
| Redaktors | Kumar, T. Ganesh (Galgotias Uni.) |
| Redaktors | Lakshmi, Venkataraman |
| Redaktors | Loret, J. B. Shajilin (FX Engineering College, India) |
| Redaktors | T. I., Manish (SCMS School and Engg and Tech, India) |
