Computational Intelligence and Healthcare Informatics. Группа авторов
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Название: Computational Intelligence and Healthcare Informatics

Автор: Группа авторов

Издательство: John Wiley & Sons Limited

Жанр: Программы

Серия:

isbn: 9781119818694

isbn:

СКАЧАТЬ on id="u9e0f3475-8afb-5f22-bf36-064d1df77c97">

      

      1  Cover

      2  Title Page

      3  Copyright

      4  Preface

      5  Part I: Introduction 1 Machine Learning and Big Data: An Approach Toward Better Healthcare Services 1.1 Introduction 1.2 Machine Learning in Healthcare 1.3 Machine Learning Algorithms 1.4 Big Data in Healthcare 1.5 Application of Big Data in Healthcare 1.6 Challenges for Big Data 1.7 Conclusion References

      6  Part II: Medical Data Processing and Analysis 2 Thoracic Image Analysis Using Deep Learning 2.1 Introduction 2.2 Broad Overview of Research 2.3 Existing Models 2.4 Comparison of Existing Models 2.5 Summary 2.6 Conclusion and Future Scope References 3 Feature Selection and Machine Learning Models for High-Dimensional Data: State-of-the-Art 3.1 Introduction 3.2 Types of Feature Selection 3.3 Machine Learning and Deep Learning Models 3.4 Real-World Applications and Scenario of Feature Selection 3.5 Conclusion References 4 A Smart Web Application for Symptom-Based Disease Detection and Prediction Using State-of-the-Art ML and ANN Models 4.1 Introduction 4.2 Literature Review 4.3 Dataset, EDA, and Data Processing 4.4 Machine Learning Algorithms 4.5 Work Architecture 4.6 Conclusion References 5 Classification of Heart Sound Signals Using Time-Frequency Image Texture Features 5.1 Introduction 5.2 Related Work 5.3 Theoretical Background 5.4 Proposed Algorithm 5.5 Experimental Results 5.6 Conclusion References 6 Improving Multi-Label Classification in Prototype Selection Scenario 6.1 Introduction 6.2 Related Work 6.3 Methodology 6.4 Performance Evaluation 6.5 Experiment Data Set 6.6 Experiment Results 6.7 Conclusion References 7 A Machine Learning–Based Intelligent Computational Framework for the Prediction of Diabetes Disease 7.1 Introduction 7.2 Materials and Methods 7.3 Machine Learning Classification Hypotheses 7.4 Classifier Validation Method 7.5 Performance Evaluation Metrics 7.6 Results and Discussion 7.7 Conclusion References 8 Hyperparameter Tuning of Ensemble Classifiers Using Grid Search and Random Search for Prediction of Heart Disease 8.1 Introduction 8.2 Related Work 8.3 Proposed Method 8.4 Experimental Outcomes and Analyses 8.5 Conclusion References 9 Computational Intelligence and Healthcare СКАЧАТЬ