Artificial Intelligence in Medicine
portes grátis
Artificial Intelligence in Medicine
Stephan, Thompson
Taylor & Francis Ltd
07/2024
252
Dura
9781032438344
Pré-lançamento - envio 15 a 20 dias após a sua edição
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List of Contributors. Part 1: Foundations of AI in Healthcare. Chapter 1: Exploring Deep Learning Approaches for Cardiac Arrhythmia Diagnosis. Chapter 2: Neural Networks and LDA based Machine Learning Framework for the Early Detection of Breast Cancer. Chapter 3: Advanced Deep Learning Algorithms for Early Ocular Disease Detection Using Fundus Images. Part 2: Disease Detection and Diagnosis. Chapter 4: A Vision Transformer-Based Approach for Brain Tumor Detection. Chapter 5: Early Detection of Skin Cancer through Human-Computer Collaboration. Chapter 6: Improved Mass Detection in Mammograms Images with Dual Tree Complex Wavelet Transform and Fourier Descriptors. Chapter 7: A Deep Learning-based Model for Early Detection of COVID-19 Using Chest X-ray Images. Chapter 8: Detection of Seizure Activity in fMRI Images Using Deep Learning Techniques. Part 3: Disease Prediction and Public Health. Chapter 9: Improving Prediction Accuracy for Neo-Adjuvant Chemotherapy Response in Breast Cancer Through 3D Image Segmentation and Deep Learning Techniques. Chapter 10: A Machine Learning Predictive Framework for Diabetes Management Using Blood Parameters. Chapter 11: A Combined Neuro-Fuzzy and Naive Bayes Approach for Swine Flu Disease Prediction System. Chapter 12: Enhancing Decision-Making in Public Maternal Healthcare using a Knowledge Discovery-Based Predictive Analytics Framework. Part 4: Patient Care and Enhancements. Chapter 13: Enhancing Patient Care and Treatment through Explainable AI: A Gap Analysis. Chapter 14: Improved Medical Image Captioning for Chest X-Rays Using a Hybrid VGG-ELECTRA Model. Chapter 15: Diagnosing Parkinson's disease using a Deep Learning Model Based on Electromyography Sensors. Chapter 16: Enhancing Heart Disease Prediction with Hybridized KNN-MOPSO Algorithm.
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artificial intelligence;medicine;AI applications;holistic healthcare
List of Contributors. Part 1: Foundations of AI in Healthcare. Chapter 1: Exploring Deep Learning Approaches for Cardiac Arrhythmia Diagnosis. Chapter 2: Neural Networks and LDA based Machine Learning Framework for the Early Detection of Breast Cancer. Chapter 3: Advanced Deep Learning Algorithms for Early Ocular Disease Detection Using Fundus Images. Part 2: Disease Detection and Diagnosis. Chapter 4: A Vision Transformer-Based Approach for Brain Tumor Detection. Chapter 5: Early Detection of Skin Cancer through Human-Computer Collaboration. Chapter 6: Improved Mass Detection in Mammograms Images with Dual Tree Complex Wavelet Transform and Fourier Descriptors. Chapter 7: A Deep Learning-based Model for Early Detection of COVID-19 Using Chest X-ray Images. Chapter 8: Detection of Seizure Activity in fMRI Images Using Deep Learning Techniques. Part 3: Disease Prediction and Public Health. Chapter 9: Improving Prediction Accuracy for Neo-Adjuvant Chemotherapy Response in Breast Cancer Through 3D Image Segmentation and Deep Learning Techniques. Chapter 10: A Machine Learning Predictive Framework for Diabetes Management Using Blood Parameters. Chapter 11: A Combined Neuro-Fuzzy and Naive Bayes Approach for Swine Flu Disease Prediction System. Chapter 12: Enhancing Decision-Making in Public Maternal Healthcare using a Knowledge Discovery-Based Predictive Analytics Framework. Part 4: Patient Care and Enhancements. Chapter 13: Enhancing Patient Care and Treatment through Explainable AI: A Gap Analysis. Chapter 14: Improved Medical Image Captioning for Chest X-Rays Using a Hybrid VGG-ELECTRA Model. Chapter 15: Diagnosing Parkinson's disease using a Deep Learning Model Based on Electromyography Sensors. Chapter 16: Enhancing Heart Disease Prediction with Hybridized KNN-MOPSO Algorithm.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
