Bioinformatics and Medical Applications. Группа авторов

9 Brain Tumor Analysis Using Deep Learning: Sensor and IoT-Based Approach for Futuristic Healthcare 9.1 Introduction 9.2 Literature Survey 9.3 System Design and Methodology 9.4 Novelty in Our Work 9.5 Future Scope, Possible Applications, and Limitations 9.6 Recommendations and Consideration 9.7 Conclusions References

      14  10 Study of Emission From Medicinal Woods to Curb Threats of Pollution and Diseases: Global Healthcare Paradigm Shift in 21st Century 10.1 Introduction 10.2 Literature Survey 10.3 The Methodology and Protocols Followed 10.4 Experimental Setup of an Experiment 10.5 Results and Discussions

      15  11 An Economical Machine Learning Approach for Anomaly Detection in IoT Environment 11.1 Introduction 11.2 Literature Survey 11.3 Proposed Work 11.4 Analysis of the Work 11.5 Conclusion References

      16  12 Indian Science of Yajna and Mantra to Cure Different Diseases: An Analysis Amidst Pandemic With a Simulated Approach 12.1 Introduction 12.2 Literature Survey 12.3 Methodology 12.4 Results and Discussion 12.5 Interpretations and Analysis 12.6 Novelty in Our Work 12.7 Recommendations 12.8 Future Scope and Possible Applications 12.9 Limitations 12.10 Conclusions 12.11 Acknowledgments References

      17  13 Collection and Analysis of Big Data From Emerging Technologies in Healthcare 13.1 Introduction 13.2 Data Collection 13.3 Data Analysis 13.4 Research Trends 13.5 Conclusion References

      18  14 A Complete Overview of Sign Language Recognition and Translation Systems 14.1 Introduction 14.2 Sign Language Recognition 14.3 Dataset Creation 14.4 Hardware Employed for Sign Language Recognition 14.5 Computer Vision–Based Sign Language Recognition and Translation Systems 14.6 Sign Language Translation System—A Brief Overview 14.7 Conclusion References

      19  Index

      20  End User License Agreement

      List of Illustrations

      1 Chapter 1Figure 1.1 Heatmap of input attributes.Figure 1.2 Age distribution.Figure 1.3 Presence of cardiovascular disease.Figure 1.4 Cholesterol type distribution.Figure 1.5 Gender distribution.Figure 1.6 Random forest algorithm.Figure 1.7 Ensemble methods.Figure 1.8 NB confusion matrix.Figure 1.9 RF confusion matrix.Figure 1.10 DT confusion matrix.Figure 1.11 ROC curve analysis.Figure 1.12 Proposed architecture.

      2 Chapter 2Figure 2.1 Framework of the experimental study of lung cancer stratification.Figure 2.2 Sample images of correctly classified and misclassified carcinoma.Figure 2.3 More sample images of correctly classified and misclassified carcinom...

      3 Chapter 3Figure 3.1 Relative frequency distribution of proteins that express the four SAR...Figure 3.2 Zoom over the Figure