Machine Learning for Healthcare Applications. Группа авторов
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10 Applications of Machine Learning in Biomedical Text Processing and Food Industry 10.1 Introduction 10.2 Use Cases of AI and ML in Healthcare 10.3 Use Cases of AI and ML in Food Technology 10.4 A Case Study: Sentiment Analysis of Drug Reviews 10.5 Results and Analysis 10.6 Conclusion References 11 Comparison of MobileNet and ResNet CNN Architectures in the CNN-Based Skin Cancer Classifier Model 11.1 Introduction 11.2 Our Skin Cancer Classifier Model 11.3 Skin Cancer Classifier Model Results 11.4 Hyperparameter Tuning and Performance 11.5 Comparative Analysis and Results 11.6 Conclusion References 12 Deep Learning-Based Image Classifier for Malaria Cell Detection 12.1 Introduction 12.2 Related Work 12.3 Proposed Work 12.4 Results and Evaluation 12.5 Conclusion References 13 Prediction of Chest Diseases Using Transfer Learning 13.1 Introduction 13.2 Types of Diseases 13.3 Diagnosis of Lung Diseases 13.4 Materials and Methods 13.5 Results and Discussions 13.6 Conclusion References 14 Early Stage Detection of Leukemia Using Artificial Intelligence 14.1 Introduction 14.2 Literature Review 14.3 Proposed Work 14.4 Conclusion and Future Aspects References
7 Part 3: INTERNET OF MEDICAL THINGS (IOMT) FOR HEALTHCARE 15 IoT Application in Interconnected Hospitals 15.1 Introduction 15.2 Networking Systems Using IoT 15.3 What are Smart Hospitals? 15.4 Assets 15.5 Threats 15.6 Conclusion References 16 Real Time Health Monitoring Using IoT With Integration of Machine Learning Approach 16.1 Introduction 16.2 Related Work 16.3 Existing Healthcare Monitoring System 16.4 Methodology and Data Analysis 16.5 Proposed System Architecture 16.6 Machine Learning Approach 16.7 Work Flow of the Proposed System 16.8 System Design of Health Monitoring System 16.9 Use Case Diagram 16.10 Conclusion References
8 Part 4: MACHINE LEARNING APPLICATIONS FOR COVID-19 17 Semantic and NLP-Based Retrieval From Covid-19 Ontology 17.1 Introduction 17.2 Related Work 17.3 Proposed Retrieval System 17.4 Conclusion References 18 Semantic Behavior Analysis of COVID-19 Patients: A Collaborative Framework 18.1 Introduction 18.2 Related Work 18.3 Methodology 18.4 Conclusion References 19 Comparative Study of Various Data Mining Techniques Towards Analysis and Prediction of Global COVID-19 Dataset 19.1 Introduction 19.2 Literature Review 19.3 Materials and Methods 19.4 Experimental Results 19.5 Conclusion and Future Scopes