Textbook in PDF format

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.
Preface
Acknowledgements
Editors and Contributors
Introduction
Domain Knowledge in Text Mining and Biomedical Data
Biomedical Data Types, Sources, Content, and Retrieval
Information Analysis Using Biomedical Text Mining
Connection and Curation of Corpus (Labeled and Unlabeled)
Biomedical Data Visualization
Biomedical Text Data Visualization
Biomedical Ontology and Model Building
Role of Ontology in Biomedical Text Mining
Ontology in Text Mining and Matching
Fundamentals of Vector-Based Text Representation and Word Embeddings
Transformer-Based Models for Text Representation and Processing
Tasks in Biomedical Text Mining
Information Retrieval and Query Expansion for Biomedical Data
Advances in Biomedical Entity and Relation Extraction: Techniques and Applications
Deep Learning for Extracting Biomedical Entities from COVID-19 Dataset: A Case Study
Multilabel Text Classification in Biomedical Domain
Biomedical Document Clustering
Knowledge Graph for Biomedical Text Mining
Exploring Knowledge Graphs (KG): A Comprehensive Overview
Building Knowledge Graphs in the Biomedical Domain: Methods and Case Studies
Applications of Biomedical Text Mining
Text Mining for Telemedicine
Text Mining for Recommendation Systems/Expert Systems in Health Domain
Agent-Based Modeling and Simulation, with Emphasis on Healthcare Data
Ethical Issues in Biomedical Text Mining