Data-Driven Diagnostics and Disease Prediction with AI Optimization provides useful insights into model creation, data preparation, and ethical issues for healthcare applications. The book covers all the conventional and non-conventional methods related to this domain. It also discusses AI-based optimization techniques, Machine Learning models, and Advanced AI, offering practical insights, case studies, and optimization strategies to help data scientists and researchers efficiently employ AI in diagnostics and illness prediction in a world where precise diagnostics and early illness prediction may save lives and healthcare resources.…mehr
Data-Driven Diagnostics and Disease Prediction with AI Optimization provides useful insights into model creation, data preparation, and ethical issues for healthcare applications. The book covers all the conventional and non-conventional methods related to this domain. It also discusses AI-based optimization techniques, Machine Learning models, and Advanced AI, offering practical insights, case studies, and optimization strategies to help data scientists and researchers efficiently employ AI in diagnostics and illness prediction in a world where precise diagnostics and early illness prediction may save lives and healthcare resources.
1. Introduction AI in Healthcare using Machine Learning and Deep Learning 2. The Importance of Diagnostics and Disease Prediction for Real World Data Sets. 3. Neural Networks and Deep Learning Frameworks 4. Deep Learning Architectures for Healthcare and Types of Healthcare Data, Data Collection and Sources 5. Data Pre-processing and Cleaning , Handling Data Privacy and Security 6. Building Machine Learning Models: Supervised Learning for Diagnostics and Unsupervised Learning for Disease Prediction 7. Building Deep Learning Models: Convolutional Neural Networks (CNNs) for image analysis from Healthcare Sectors 8. Recurrent Neural Networks (RNNs) for time-series data Transfer learning and pretrained models 9. Natural Language Processing for Healthcare Texts 10. Predictive Modeling for Early Disease Detection 11. Telemedicine and Remote Diagnostics 12. Ensuring Patient Privacy, Informed Consent, Ethical and Regulatory Considerations 13. Future Trends and Innovations in Healthcare AI, Quantum Computing, and Edge Computing 14. Multimodal Data Fusion for Enhanced Diagnostics
1. Introduction AI in Healthcare using Machine Learning and Deep Learning 2. The Importance of Diagnostics and Disease Prediction for Real World Data Sets. 3. Neural Networks and Deep Learning Frameworks 4. Deep Learning Architectures for Healthcare and Types of Healthcare Data, Data Collection and Sources 5. Data Pre-processing and Cleaning , Handling Data Privacy and Security 6. Building Machine Learning Models: Supervised Learning for Diagnostics and Unsupervised Learning for Disease Prediction 7. Building Deep Learning Models: Convolutional Neural Networks (CNNs) for image analysis from Healthcare Sectors 8. Recurrent Neural Networks (RNNs) for time-series data Transfer learning and pretrained models 9. Natural Language Processing for Healthcare Texts 10. Predictive Modeling for Early Disease Detection 11. Telemedicine and Remote Diagnostics 12. Ensuring Patient Privacy, Informed Consent, Ethical and Regulatory Considerations 13. Future Trends and Innovations in Healthcare AI, Quantum Computing, and Edge Computing 14. Multimodal Data Fusion for Enhanced Diagnostics
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Internetauftritt der buecher.de internetstores GmbH
Geschäftsführung: Monica Sawhney | Roland Kölbl | Günter Hilger
Sitz der Gesellschaft: Batheyer Straße 115 - 117, 58099 Hagen
Postanschrift: Bürgermeister-Wegele-Str. 12, 86167 Augsburg
Amtsgericht Hagen HRB 13257
Steuernummer: 321/5800/1497
USt-IdNr: DE450055826