Description
Applications of Artificial Intelligence in Healthcare and Biomedicine provides updated knowledge on the applications of artificial intelligence in medical image analysis. The book starts with an introduction to Artificial Intelligence techniques for Healthcare and Biomedicine.In 16 chapters it presents artificial applications in Electrocardiogram (ECG), Electroencephalogram (EEG) and Electromyography (EMG), signal analysis, Computed Tomography (CT), Magnetic Resonance Imaging (MR) and Ultrasound image analysis. It equips researchers with tools for early breast cancer detection from mammograms using artificial intelligence (AI), AI models to detect lung cancer using histopathological images and a deep learning-based approach to get a proper and faster diagnosis of the Optical Coherence Tomography (OCT) images. It also presents present 3D medical image analysis using 3D Convolutional Neural Networks (CNNs). Applications of Artificial Intelligence in Healthcare and Biomedicine closes with a chapter on AI-based approach to forecast diabetes patients' hospital re-admissions.This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about the applications of Artificial Intelligence and its impact in medical/biomedical image analysis.- Provides knowledge on Artificial Intelligence algorithms for clinical data analysis- Gives insights into both AI applications in biomedical signal analysis, biomedical image analysis, and applications in healthcare, including drug discovery- Equips researchers with tools for early breast cancer detection
Table of Contents
1. AI techniques for healthcare and biomedicineABDULHAMIT SUBASI2. Artificial intelligence-based emotion recognition using ECG signalsFADIME TOKMAK, ABDULHAMIT SUBASI, AND SAEED MIAN QAISAR3. Artificial intelligence-based depression detection using EEG signalsFADIME TOKMAK AND ABDULHAMIT SUBASI4. Electromyography signal classification using artificial intelligenceABDULHAMIT SUBASI5. An evaluation of pretrained convolutional neural networks for stroke classification from brain CT imagesMUHAMMAD IRFAN, ABDULHAMIT SUBASI, NOMAN MUSTAFA, TOMI WESTERLUND, AND WEI CHEN6. Brain tumor detection using deep learning from magnetic resonance imagesEMAN HASSANAIN AND ABDULHAMIT SUBASI7. Artificial intelligence-based fatty liver disease detection using ultrasound imagesSAFDAR WAHID INAMDAR AND ABDULHAMIT SUBASI8. Deep learning approaches for breast cancer detection using breast MRITANISHA SAHU AND ABDULHAMIT SUBASI9. Automated detection of colon cancer from histopathological images using deep neural networksMIRKA SUOMINEN, MUHAMMED ENES SUBASI, AND ABDULHAMIT SUBASI10. Optical coherence tomography image classification for retinal disease detection using artificial intelligenceMUHAMMED ENES SUBASI, SOHAN PATNAIK, AND ABDULHAMIT SUBASI11. Heart muscles inflammation (myocarditis) detection using artificial intelligenceRUPAL SHAH AND ABDULHAMIT SUBASI12. Artificial intelligence for 3D medical image analysisABDULHAMIT SUBASI13. Medical image segmentation using artificial intelligenceABDULHAMIT SUBASI14. DNA sequence classification using artificial intelligenceABDULHAMIT SUBASI15. Artificial intelligence in drug discovery and developmentABDULHAMIT SUBASI16. Hospital readmission forecasting using artificial intelligenceABDULHAMIT SUBASI
