Computational Intelligence in Medical Decision Making and Diagnosis
portes grátis
Computational Intelligence in Medical Decision Making and Diagnosis
Techniques and Applications
Choubey, Shruti Bhargava; Choubey, Abhishek; Tamrakar, Sitendra
Taylor & Francis Ltd
10/2024
268
Mole
9781032313788
Pré-lançamento - envio 15 a 20 dias após a sua edição
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1 Prediction of Diseases Using Machine Learning Techniques; 2 A Novel Virtual Medicinal Care Model for Remote Treatments; 3 Artificial Intelligence in Future Telepsychiatry and Psychotherapy for E-Mental Health Revolution; 4 Optimized Convolutional Neural Network for Classification of Tumors from MR Brain Images; 5 Predictive Modeling of Epidemic Diseases Based on Vector-Borne Diseases Using Artificial Intelligence Techniques; 6 Hybrid Neural Network-Based Fuzzy Inference System Combined with Machine Learning to Detect and Segment Kidney Tumor; 7 Classification of Breast Tumor from Histopathological Images with Transfer Learning; 8 Performance of IoT-Enabled Devices in Remote Health Monitoring Applications; 9 Applying Machine Learning Logistic Regression Model for Predicting Diabetes in Women; 10 Compressive Sensing-Based Medical Imaging Techniques to Detect the Type of Pneumonia in Lungs; 11 Electroencephalogram (EEG) Signal Denoising Using Optimized Wavelet Transform (WT): A Study; 12 Predicting Diabetes in Women by Applying the Support Vector Machine (SVM) Model; 13 Data Mining Approaches on EHR System: A Survey; 14 Chest Tumor Identification in Mammograms by Selected Features Employing SVM; 15 A Novel Optimum Clustering Method Using Variant of NOA; 16 Role of Artificial Intelligence and Neural Network in the Health-Care Sector: An Important Guide for Health Prominence
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Data Mining;Artificial Intelligence;Neuro-Fuzzy;Swarm Optimization;Deep Learning;Glaucoma;Diabetes;Medical Imaging;SSIM;STA Model;Max Pooling Layer;E-mental Health;EEG Signal Processing;SVM;CT Scan Image;Convolutional Layers;Ml Model;Convolutional Neural Network Model;EEG Signal;Ml Algorithm;Vector Borne Diseases;Deep Learning Algorithms;Data Frame;CS;IoT Device;Multimodal Benchmark Functions;Polynomial Kernel;SSIM Value;Proposed Clustering Method;SVM Algorithm;Histopathological Images;Metaheuristic Algorithms;Multinomial Logistic Regression
1 Prediction of Diseases Using Machine Learning Techniques; 2 A Novel Virtual Medicinal Care Model for Remote Treatments; 3 Artificial Intelligence in Future Telepsychiatry and Psychotherapy for E-Mental Health Revolution; 4 Optimized Convolutional Neural Network for Classification of Tumors from MR Brain Images; 5 Predictive Modeling of Epidemic Diseases Based on Vector-Borne Diseases Using Artificial Intelligence Techniques; 6 Hybrid Neural Network-Based Fuzzy Inference System Combined with Machine Learning to Detect and Segment Kidney Tumor; 7 Classification of Breast Tumor from Histopathological Images with Transfer Learning; 8 Performance of IoT-Enabled Devices in Remote Health Monitoring Applications; 9 Applying Machine Learning Logistic Regression Model for Predicting Diabetes in Women; 10 Compressive Sensing-Based Medical Imaging Techniques to Detect the Type of Pneumonia in Lungs; 11 Electroencephalogram (EEG) Signal Denoising Using Optimized Wavelet Transform (WT): A Study; 12 Predicting Diabetes in Women by Applying the Support Vector Machine (SVM) Model; 13 Data Mining Approaches on EHR System: A Survey; 14 Chest Tumor Identification in Mammograms by Selected Features Employing SVM; 15 A Novel Optimum Clustering Method Using Variant of NOA; 16 Role of Artificial Intelligence and Neural Network in the Health-Care Sector: An Important Guide for Health Prominence
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Data Mining;Artificial Intelligence;Neuro-Fuzzy;Swarm Optimization;Deep Learning;Glaucoma;Diabetes;Medical Imaging;SSIM;STA Model;Max Pooling Layer;E-mental Health;EEG Signal Processing;SVM;CT Scan Image;Convolutional Layers;Ml Model;Convolutional Neural Network Model;EEG Signal;Ml Algorithm;Vector Borne Diseases;Deep Learning Algorithms;Data Frame;CS;IoT Device;Multimodal Benchmark Functions;Polynomial Kernel;SSIM Value;Proposed Clustering Method;SVM Algorithm;Histopathological Images;Metaheuristic Algorithms;Multinomial Logistic Regression
