It is widely believed that Artificial Intelligence (AI) and its applications will revolutionize healthcare and medicine. This book provides a comprehensive overview on the recent developments on clinical decision support systems, precision health and data science in medicine.
It is widely believed that Artificial Intelligence (AI) and its applications will revolutionize healthcare and medicine. This book provides a comprehensive overview on the recent developments on clinical decision support systems, precision health and data science in medicine.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Professor Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY and the former Chair of Cyber Security, University of York. Enrique Domínguez is an associate professor at the department of Computer Science at the University of Malaga and a member of Biomedic Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.
Inhaltsangabe
1. Machine learning for disease classification: A perspective. 2. A review of automatic cardiac segmentation using deep learning and deformable models. 3. Advances in artificial intelligence applied to heart failure. 4. A Combination of Dilated Adversarial Convolutional Neural Network and Guided Active Contour Model for Left Ventricle Segmentation. 5. Automated methods for vessel segmentation in X-ray coronary angiography and geometric modeling of coronary angiographic image sequences: a survey. 6. Super-Resolution of 3D Magnetic Resonance Images of the Brain. 7. Head CT analysis for intracranial hemorrhage segmentation. 8. Wound Tissue Classification with Convolutional Neural Networks. 9. Artificial Intelligence Methodologies in Dentistry. 10. Literature Review of Computer Tools for the Visually Impaired: A Focus on Search Engines. 11. Tensor methods for clinical informatics.
1. Machine learning for disease classification: A perspective. 2. A review of automatic cardiac segmentation using deep learning and deformable models. 3. Advances in artificial intelligence applied to heart failure. 4. A Combination of Dilated Adversarial Convolutional Neural Network and Guided Active Contour Model for Left Ventricle Segmentation. 5. Automated methods for vessel segmentation in X-ray coronary angiography and geometric modeling of coronary angiographic image sequences: a survey. 6. Super-Resolution of 3D Magnetic Resonance Images of the Brain. 7. Head CT analysis for intracranial hemorrhage segmentation. 8. Wound Tissue Classification with Convolutional Neural Networks. 9. Artificial Intelligence Methodologies in Dentistry. 10. Literature Review of Computer Tools for the Visually Impaired: A Focus on Search Engines. 11. Tensor methods for clinical informatics.
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