Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder

Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder

Release Date: June, 2021|Copyright: © 2021 |Pages: 224
DOI: 10.4018/978-1-7998-7460-7
ISBN13: 9781799874607|ISBN10: 1799874605|EISBN13: 9781799874621
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Description & Coverage
Description:

Autism spectrum disorder (ASD) is known as a neuro-disorder in which a person may face problems in interaction and communication with people, amongst other challenges. As per medical experts, ASD can be diagnosed at any stage or age but is often noticeable within the first two years of life. If caught early enough, therapies and services can be provided at this early stage instead of waiting until it is too late. ASD occurrences appear to have increased over the last couple of years leading to the need for more research in the field. It is crucial to provide researchers and clinicians with the most up-to-date information on the clinical features, etiopathogenesis, and therapeutic strategies for patients as well as to shed light on the other psychiatric conditions often associated with ASD. In addition, it is equally important to understand how to detect ASD in individuals for accurate diagnosing and early detection.

Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder discusses the early detection and diagnosis of autism spectrum disorder enabled by artificial intelligence technologies, applications, and therapies. This book will focus on the early diagnosis of ASD through artificial intelligence, such as deep learning and machine learning algorithms, for confirming diagnosis or suggesting the need for further evaluation of individuals. The chapters will also discuss the use of artificial intelligence technologies, such as medical robots, for enhancing the communication skills and the social and emotional skills of children who have been diagnosed with ASD. This book is ideally intended for IT specialists, data scientists, academicians, scholars, researchers, policymakers, medical practitioners, and students interested in how artificial intelligence is impacting the diagnosis and treatment of autism spectrum disorder.

Coverage:

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

  • AI-Aided Diagnosis Methods
  • Artificial Intelligence
  • ASD Therapies
  • Autism Spectrum Disorder (ASD)
  • Child Development
  • Early Diagnosis of ASD
  • Early Intervention
  • Machine Learning
  • Medical imaging
  • Medical Robotics
  • Predictive Analysis for ASD
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Editor/Author Biographies

Sandeep Kautish is working as Professor & Dean-Academics with LBEF Campus, Kathmandu Nepal running in academic collaboration with Asia Pacific University of Technology & Innovation Malaysia. He is an academician by choice and backed with 17+ Years of work experience in academics including over 06 years in academic administration in various institutions of India and abroad. He has meritorious academic records throughout his academic career. He earned his bachelors, masters and doctorate degree in Computer Science on Intelligent Systems in Social Networks. He holds PG Diploma in Management also. His areas of research interest are Business Analytics, Machine Learning, Data Mining, and Information Systems. He has 40+ publications in his account and his research works has been published in reputed journals with high impact factor and SCI/SCIE/Scopus/WoS indexing. His research papers can be found at Computer Standards & Interfaces (SCI, Elsevier), Journal of Ambient Intelligence and Humanized Computing (SCIE, Springer). Also, he has authored/edited more than 07 books with reputed publishers i.e. Springer, Elsevier, Scrivener Wiley, De Gruyter, and IGI Global. He has been invited as Keynote Speaker at VIT Vellore (QS ranking with 801-1000) in 2019 for an International Virtual Conference. He filed one patent in the field of Solar Energy equipment using Artificial Intelligence in 2019. He is an editorial member/reviewer of various reputed SCI/SCIE journals i.e. Computer Communications (Elsevier), ACM Transactions on Internet Technology, Cluster Computing (Springer), Neural Computing and Applications (Springer), Journal of Intelligent Manufacturing (Springer), Multimedia Tools & Applications (Springer), Computational Intelligence (Wiley), Australasian Journal of Information Systems (AJIS, International Journal of Decision Support System Technology (IGI Global USA), International Journal of Image Mining (Inderscience). He has supervised one PhD in Computer Science as a co-supervisor at Bharathiar University Coimbatore. Presently two doctoral scholars are pursuing their PhD under his supervision in different application areas of Machine Learning. He is a recognized academician as Session Chair/PhD thesis examiner at various international universities of reputes i.e. University of Kufa, University of Babylon, Polytechnic University of the Philippines (PUP), University of Madras, Anna University Chennai, Savitribai Phule Pune University, M.S. University, Tirunelveli, and various other Technical Universities.

Gaurav Dhiman is an Assistant Professor within the Department of Computer Science, Government Bikram College of Commerce, Patiala. The editor’s current research interests include bio-inspired and evolutionary-based metaheuristic techniques for solving single-, multi-, and many-objective large-scale complex problems.
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