AI Applications for Disease Diagnosis and Treatment

AI Applications for Disease Diagnosis and Treatment

Release Date: June, 2022|Copyright: © 2022 |Pages: 332
DOI: 10.4018/978-1-6684-2304-2
ISBN13: 9781668423042|ISBN10: 1668423049|EISBN13: 9781668423066
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Description & Coverage
Description:

Artificial intelligence (AI) technology has been very successful across fields such as healthcare, security, precision agriculture, smart city, and autonomous driving and promises numerous benefits for social development, economic growth, wellbeing management, and human healthcare. Various intelligent healthcare applications have been created in order to assist patient healthcare and must be studied further.

AI Applications for Disease Diagnosis and Treatment provides the current advances and applications of artificial intelligence applications in healthcare such as disease diagnosis, diet proposal, drug prescription and tracking, and physical and psychological assistance. Covering topics such as assistive healthcare, robotics, and machine learning, it is ideal for healthcare professionals, researchers, data analysts, academicians, practitioners, scholars, instructors, and students.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Assistive Healthcare
  • Biometrics
  • Deep Learning
  • Disease Detection
  • Evolutionary Computing
  • Machine Learning
  • Medical Screening
  • Natural Language Processing
  • Neuroinformatics
  • Robotics
Reviews & Statements

The book that is recommended delves into the most cutting-edge uses of artificial intelligence (AI) in medical diagnosis and therapy. It provides a thorough and informative examination of how AI innovations are changing the healthcare industry and advancing disease detection, diagnosis, and personalized treatment methods. The book highlights real-world case studies and the revolutionary potential of AI in tackling diverse medical difficulties.

For scientists, academics, and tech enthusiasts wanting to comprehend and realize the promise of AI in the healthcare industry, the book of applications for disease detection and treatment achieves to be a vital resource. The book encourages readers to use AI's transformational power ethically, which will ultimately result in better patient care, early disease detection, and improved treatment outcomes. It does this by displaying real-world instances and addressing ethical issues.

– Elmustafa Sayed Ali Ahmed, Red Sea University
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Editor/Author Biographies

Rajae El Ouazzani received her PhD in Image and Video Processing from the High National School of Computer Science and Systems Analysis (ENSIAS-Morocco) in 2010 and the Master’s degree in Computer Science and Telecommunication from the Mohammed V University of Rabat (FSR-Morocco) in 2006. From 2011, she is a Professor in the School of Technology of Meknes, Moulay Ismail University in Morocco. Since 2007, she is the author of several papers in international conferences and journals. Her domains of interest include AI, multimedia processing, and NLP.

Mohammed Fattah received his Ph.D. degree in Telecommunication Engineering from the University of Sidi Mohamed Ben Abdellah (USMBA) Fez, Morocco, 2011. He is currently working as Professor in the Electrical Engineering Department at the school of technology of Moulay Ismail University (UMI), Meknes, Morocco. He is a responsible of the research team ‘Intelligent Systems, Networks and Telecommunications’, IMAGE laboratory of UMI. His current research interests include cloud computing, machine learning, radio mobile networks, body sensor networks, medical of things and IoT, mm-wave and THz communication systems. He has authored or coauthored more than 40 papers in different peer-reviewed journals and conferences. He is Guest Editor of Mathematical Problems in Engineering Journal, and Big Data Mining and Analytics Journal. He is a reviewer for peer-reviewed research journals.

Nabil Benamar is a full professor of Computer Sciences at the School of Technology, Moulay Ismail University of Meknes. He holds a Ph.D. in Sciences from Faculty of Sciences-Meknes (2004), a Master degree in Physics (2001) and a Master degree in Computer Networks (INPT 2003). His main research topics are IPv6, IoT, Intelligent Transport Systems, Autonomous Driving, and Next Generation Networks. He is the author of several journal papers in highly ranked journals as well as IETF Standard documents. He is currently serving as an Associate Editor of the “IEEE Access” and the “Wireless Communications and Mobile computing” journals, and reviewer for several IEEE, Elsevier, Wiley and Springer journals. Dr. Benamar is a TPC member of different IEEE Flagship conferences (Globecom, ICC, PIMRC, WCNC, etc..), and a member of the Organizing Committee of WCNC'2019. Furthermore, He is an IPv6 expert (he.net certified) and IPv6 trainer with many international organizations (RIPE/MENOG, AFRINIC, and Agence Universitaire de Francophonie). He became an expert in Internet Governance after completion of ISOC Next generation e-learning programme. He has been selected as an ISOC Ambassador to IGF(2012 and 2013), Google panelist in the first Arab-IGF, ISOC fellow to IETF'89&92&95&99&103 and ICANN'50&54 fellow. Among his commitments, he is chairing the Task Force for Arabic IDNs which is a part of Global Stakeholder Engagement (GSE) of ICANN a team of people working on making the DNS speaks Arabic and enabling Email address Internationalization. He is the chair of the UASG measurement WG, an ICANN initiative for ensuring Universal Acceptance.

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