Current Applications of Deep Learning in Cancer Diagnostics
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Current Applications of Deep Learning in Cancer Diagnostics
Ucar, Aysegul; Chaki, Jyotismita
Taylor & Francis Ltd
10/2024
167
Mole
9781032223193
Pré-lançamento - envio 15 a 20 dias após a sua edição
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1. Contemporary Trends in the Early Detection and Diagnosis of Human Cancers Using Deep Learning Techniques, 2. Cancer Data Pre-Processing Techniques, 3. A Survey on Deep Learning Techniques for Breast, Leukemia and Cervical Cancer Prediction, 4. An Optimized Deep Learning Technique for Detecting Lung Cancer from CT Images, 5. Brain Tumor Segmentation Utilizing MRI Multimodal Images with Deep Learning, 6. Detection and Classification of Brain Tumors Using Light-Weight Convolutional Neural Network, 7. Parallel Dense Skip Connected CNN Approach for Brain Tumor Classification, 8. Liver Tumor Segmentation Using Deep Learning Neural Networks, 9. Deep Learning Algorithms for Classification and Prediction of Acute Lymphoblastic Leukemia, 10. Cervical Pap Smear Screening and Cancer Detection Using Deep Neural Network, 11. Cancer Detection Using Deep Neural Network: Differentiation of Squamous Carcinoma Cells in Oral Pathology, 12. Challenges and Future Scopes in Current Applications of Deep Learning in Human Cancer Diagnostics
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cancer diagnostics;cancer;deep learning;Leukemia;Cervical Cancer;Breast Cancer;CT images;Brain tumor;Light Weight Convolutional Neural Network;Deep Learning Neural Networks;Human Cancer Diagnostics;Allogeneic Hematopoietic Stem Cell Transplantation;Stacked Auto Encoder;SVM RFE;CNN Model;Deep Learning Algorithms;Roc Curve;CNN Architecture;Pap Smear;Deep Learning Methods;Mri Dataset;NN Model;Cad System;Tumor Segmentation;Data Set;HSI Color Space;Tumor Dataset;Small 2C;Data Augmentation;Mri Brain Image;T2 Weight Mri Scan;Dice Score;BRCA2 Gene Mutation
1. Contemporary Trends in the Early Detection and Diagnosis of Human Cancers Using Deep Learning Techniques, 2. Cancer Data Pre-Processing Techniques, 3. A Survey on Deep Learning Techniques for Breast, Leukemia and Cervical Cancer Prediction, 4. An Optimized Deep Learning Technique for Detecting Lung Cancer from CT Images, 5. Brain Tumor Segmentation Utilizing MRI Multimodal Images with Deep Learning, 6. Detection and Classification of Brain Tumors Using Light-Weight Convolutional Neural Network, 7. Parallel Dense Skip Connected CNN Approach for Brain Tumor Classification, 8. Liver Tumor Segmentation Using Deep Learning Neural Networks, 9. Deep Learning Algorithms for Classification and Prediction of Acute Lymphoblastic Leukemia, 10. Cervical Pap Smear Screening and Cancer Detection Using Deep Neural Network, 11. Cancer Detection Using Deep Neural Network: Differentiation of Squamous Carcinoma Cells in Oral Pathology, 12. Challenges and Future Scopes in Current Applications of Deep Learning in Human Cancer Diagnostics
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
cancer diagnostics;cancer;deep learning;Leukemia;Cervical Cancer;Breast Cancer;CT images;Brain tumor;Light Weight Convolutional Neural Network;Deep Learning Neural Networks;Human Cancer Diagnostics;Allogeneic Hematopoietic Stem Cell Transplantation;Stacked Auto Encoder;SVM RFE;CNN Model;Deep Learning Algorithms;Roc Curve;CNN Architecture;Pap Smear;Deep Learning Methods;Mri Dataset;NN Model;Cad System;Tumor Segmentation;Data Set;HSI Color Space;Tumor Dataset;Small 2C;Data Augmentation;Mri Brain Image;T2 Weight Mri Scan;Dice Score;BRCA2 Gene Mutation
