Deep Learning for Medical Applications with Unique Data
Editat de Deepak Gupta, Utku Kose, Ashish Khanna, Valentina Emilia Balasen Limba Engleză Paperback – 17 feb 2022
- Introduces deep learning, demonstrating concepts for a wide variety of medical applications using unique data, excluding research with ready datasets
- Encompasses a wide variety of biomedical applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing and disease diagnosis
- Provides a robust set of methods that will help readers appropriately and judiciously use the most suitable deep learning techniques for their applications
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Specificații
ISBN-13: 9780128241455
ISBN-10: 0128241454
Pagini: 256
Ilustrații: 60 illustrations (20 in full color)
Dimensiuni: 191 x 235 x 21 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0128241454
Pagini: 256
Ilustrații: 60 illustrations (20 in full color)
Dimensiuni: 191 x 235 x 21 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
Public țintă
Biomedical engineers and researchers in biomedical engineering, applied informatics, Artificial Intelligence, and data science. Computer scientists, as well as students in electronics, communication engineering, and information technology.Cuprins
1. A deep learning approach for the prediction of heart attacks based on data analysis 2. A comparative study on fully convolutional networks—FCN-8, FCN-16, and FCN-32: A case of brain tumor 3. Deep learning applications for disease diagnosis 4. An artificial intelligent cognitive approach for classification and recognition of white blood cells employing deep learning for medical applications 5. Deep learning on medical image analysis on COVID-19 x-ray dataset using an X-Net architecture 6. Early prediction of heart disease using a deep learning approach 7. Machine learning and deep learning algorithms in disease prediction: Future trends for the healthcare system 8. Automatic detection of white matter hyperintensities via mask region-based convolutional neural networks using magnetic resonance images 9. Diagnosing glaucoma with optic disk segmenting and deep learning from color retinal fundus images 10. An artificial intelligence framework to ensure a trade-off between sanitary and economic perspectives during the COVID-19 pandemic 11. Prediction of COVID-19 using machine learning techniques