Overview

Artificial Intelligence (AI) has become a transformative force in the biomedical field, offering powerful tools to analyze complex data, enhance diagnostics, and support personalized medicine. Machine learning algorithms can identify patterns in genomic data for disease prediction, while deep learning models excel in medical imaging, detecting conditions like cancer or neurological disorders with high accuracy. NLP enables insights from clinical records, supporting decision-making and automating administrative tasks. Meanwhile, AI-powered robotics and smart sensors enhance surgical precision and patient monitoring. Further research of these applications may improve patient outcomes and streamline healthcare systems. Techniques and Applications of Biomedical AI delves into the rapidly evolving field of prompt engineering, specifically within the context of biomedical AI. It addresses both the theoretical foundations and practical applications of prompt engineering, highlighting its potential to revolutionize healthcare and biomedical research. This book covers topics such as biology, medical technologies, and risk management, and is a useful resource for biologists, medical and healthcare professionals, engineers, academicians, researchers, and scientists.

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Hatem Abdulkader received the B.Sc. and M.Sc. (by Research) degrees in electrical engineering from the Faculty of Engineering, Alexandria University, Egypt, in 1990 and 1995, respectively, and the Ph.D. degree in electrical engineering from the Faculty of Engineering, Alexandria University, in 2001, specializing in neural networks and applications. He is currently a Professor with the Information Systems Department, Faculty of Computers and Information, Menoufia University, since 2004. He has worked on a number of organizations. He has contributed more than 150 technical articles in the areas of neural networks, big data, database applications, information security, and internet applications.

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