| 000 | 02397 a2200493 4500 | ||
|---|---|---|---|
| 001 | 1040305695 | ||
| 005 | 20250328151419.0 | ||
| 008 | 250324022025xx 258 eng | ||
| 020 |
_a9781040305690 _qEA |
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| 037 |
_bTaylor & Francis _cGBP 49.99 _fBB |
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| 040 | _a01 | ||
| 041 | _aeng | ||
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| 100 | 1 | _aP. Mohamed Fathimal | |
| 245 | 1 | 0 | _aAdvances of Machine Learning for Knowledge Mining in Electronic Health Records |
| 250 | _a1 | ||
| 260 |
_bChapman and Hall/CRC _c20250307 |
||
| 300 | _a284 p | ||
| 520 | _bThe 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, with a focus on the design and representation of structured, semi-structured, and unstructured data. Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health records Covers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured data Discusses supervised and unsupervised learning in electronic health records Describes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health records This book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning. | ||
| 700 | 1 |
_aT. Ganesh Kumar _4B01 |
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| 700 | 1 |
_aJ. B. Shajilin Loret _4B01 |
|
| 700 | 1 |
_aVenkataraman Lakshmi _4B01 |
|
| 700 | 1 |
_aManish T. I. _4B01 |
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| 999 |
_c8004 _d8004 |
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