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Applications of Artificial Intelligence in Healthcare and Biomedicine

Abdulhamit Subasi (Full Professor, University of Turku, Finland)

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English
Academic Press Inc
22 March 2024
Applications of Artificial Intelligence in Healthcare and Biomedicine provides ?updated knowledge on the applications of artificial intelligence in medical image analysis. 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 image,

and a deep learning-based approach to get a proper and faster diagnosis of the Optical Coherence Tomography (OCT) images.

In addition, it presents 3D medical image analysis using 3D Convolutional Neural Networks (CNNs). Final sections cover an 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.

By:  
Imprint:   Academic Press Inc
Country of Publication:   United States
Weight:   450g
ISBN:   9780443223082
ISBN 10:   0443223084
Series:   Artificial Intelligence Applications in Healthcare and Medicine
Pages:   548
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
1. AI techniques for healthcare and biomedicine ABDULHAMIT SUBASI 2. Artificial intelligence-based emotion recognition using ECG signals FADIME TOKMAK, ABDULHAMIT SUBASI, AND SAEED MIAN QAISAR 3. Artificial intelligence-based depression detection using EEG signals FADIME TOKMAK AND ABDULHAMIT SUBASI 4. Electromyography signal classification using artificial intelligence ABDULHAMIT SUBASI 5. An evaluation of pretrained convolutional neural networks for stroke classification from brain CT images MUHAMMAD IRFAN, ABDULHAMIT SUBASI, NOMAN MUSTAFA, TOMI WESTERLUND, AND WEI CHEN 6. Brain tumor detection using deep learning from magnetic resonance images EMAN HASSANAIN AND ABDULHAMIT SUBASI 7. Artificial intelligence-based fatty liver disease detection using ultrasound images SAFDAR WAHID INAMDAR AND ABDULHAMIT SUBASI 8. Deep learning approaches for breast cancer detection using breast MRI TANISHA SAHU AND ABDULHAMIT SUBASI 9. Automated detection of colon cancer from histopathological images using deep neural networks MIRKA SUOMINEN, MUHAMMED ENES SUBASI, AND ABDULHAMIT SUBASI 10. Optical coherence tomography image classification for retinal disease detection using artificial intelligence MUHAMMED ENES SUBASI, SOHAN PATNAIK, AND ABDULHAMIT SUBASI 11. Heart muscles inflammation (myocarditis) detection using artificial intelligence RUPAL SHAH AND ABDULHAMIT SUBASI 12. Artificial intelligence for 3D medical image analysis ABDULHAMIT SUBASI 13. Medical image segmentation using artificial intelligence ABDULHAMIT SUBASI 14. DNA sequence classification using artificial intelligence ABDULHAMIT SUBASI 15. Artificial intelligence in drug discovery and development ABDULHAMIT SUBASI 16. Hospital readmission forecasting using artificial intelligence ABDULHAMIT SUBASI

Abdulhamit Subasi is a highly specialized expert in the fields of Artificial Intelligence, Machine Learning, and Biomedical Signal and Image Processing. His extensive expertise in applying machine learning across diverse domains is evident in his numerous contributions, including the authorship of multiple book chapters, as well as the publication of a substantial body of research in esteemed journals and conferences. His career has spanned various prestigious institutions, including the Georgia Institute of Technology in Georgia, USA, where he served as a dedicated researcher. In recognition of his outstanding research contributions, Subasi received the prestigious Queen Effat Award for Excellence in Research in May 2018. His academic journey includes a tenure as a Professor of computer science at Effat University in Jeddah, Saudi Arabia, from 2015 to 2020. Since 2020, he has assumed the role of Professor of medical physics at the Faculty of Medicine, University of Turku in Turku, Finland

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