Text Mining Approaches for Biomedical Data (eBook)
XV, 440 Seiten
Springer Nature Singapore (Verlag)
978-981-97-3962-2 (ISBN)
The book 'Text Mining Approaches for Biomedical Data' delves into the fascinating realm of text mining in healthcare. It provides an in-depth understanding of how Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing healthcare research and patient care. The book covers a wide range of topics such as mining textual data in biomedical and health databases, analyzing literature and clinical trials, and demonstrating various applications of text mining in healthcare.
This book is a guide for effectively representing textual data using vectors, knowledge graphs, and other advanced techniques. It covers various text mining applications, building descriptive and predictive models, and evaluating them. Additionally, it includes building machine learning models using textual data, covering statistical and deep learning approaches.
This book is designed to be a valuable reference for computer science professionals, researchers in the biomedical field, and clinicians. It provides practical guidance and promotes collaboration between different disciplines. Therefore, it is a must-read for anyone who is interested in the intersection of text mining and healthcare.
The book 'Text Mining Approaches for Biomedical Data' delves into the fascinating realm of text mining in healthcare. It provides an in-depth understanding of how Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing healthcare research and patient care. The book covers a wide range of topics such as mining textual data in biomedical and health databases, analyzing literature and clinical trials, and demonstrating various applications of text mining in healthcare.This book is a guide for effectively representing textual data using vectors, knowledge graphs, and other advanced techniques. It covers various text mining applications, building descriptive and predictive models, and evaluating them. Additionally, it includes building machine learning models using textual data, covering statistical and deep learning approaches.This book is designed to be a valuable reference for computer science professionals, researchers in the biomedical field, and clinicians. It provides practical guidance and promotes collaboration between different disciplines. Therefore, it is a must-read for anyone who is interested in the intersection of text mining and healthcare.
| Erscheint lt. Verlag | 3.9.2024 |
|---|---|
| Reihe/Serie | Transactions on Computer Systems and Networks |
| Zusatzinfo | XV, 440 p. 166 illus., 123 illus. in color. |
| Sprache | englisch |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| Medizin / Pharmazie ► Pflege | |
| Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
| Technik ► Medizintechnik | |
| Schlagworte | Biomedical document classification • Biomedical entity extraction • biomedical informatics • Biomedical knowledge graphs • biomedical ontologies • Biomedical text mining • Expert Systems • Information retrieval in biomedical domain • knowledge graphs • machine learning |
| ISBN-10 | 981-97-3962-4 / 9819739624 |
| ISBN-13 | 978-981-97-3962-2 / 9789819739622 |
| Haben Sie eine Frage zum Produkt? |
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