Artificial Intelligence Applications in a Pandemic
- Available for pre-order. Item will ship after October 12, 2021
COVID-19, a novel coronavirus pandemic has disrupted our society in many ways. Digital healthcare innovations are required more than ever before as we come across myriad challenges during this pandemic. Scientists and developers are learning and finding a way to use artificial intelligence applications and natural language processing to comprehend and tackle this disease.
AI technologies are playing an important role in the response to the COVID-19 pandemic. Experts are using all possible tools to study the virus, diagnose individuals, and analyze the public health impacts. This book is a collection of some of the leading efforts related to AI and COVID-19 focused on finding how AI can be helpful in monitoring the situation from early warnings, swift emergency responses, and critical decision-making. It discusses the use of machine learning and how it may help to reduce the impacts of this pandemic in conjunction with all other research and strategies going on. The book serves as a technical resource of data analytics and AI applications in tracking infectious diseases. It will serve academics, students, data scientists, medical practitioners, and anybody managing a global pandemic.
- Directs the attention to the smart digital healthcare system in this COVID-19 pandemic.
- Simulates novel investigations and how they will be beneficial in understanding the pandemic.
- Presents the latest ideas developed for data scientists, doctors, engineers, and economists.
- Analyses the various issues related to computing, AI apps, big data analytic techniques, and predictive scientific skill gaps.
- Explains some interesting and diverse types of challenges and data-driven healthcare applications.
Table of Contents
- Role of Artificial Intelligence in COVID-19
- Application of 3D printing in COVID-19
- Role of IoT and AI in Covid-19
- Potential contributions of AI against COVID-19
- Dynamic Animated Plots for Better COVID Cases Analysis: Line, Bar, Bubble Plots using R Programming
- A Comparative Study of COVID -19 Data Analysis using R Programming (a SIR Model Prediction)
- Tracking and Analyzing COVID-19 pandemic using Twitter and Topic Modelling
- Artificial Neural Network Application to Analyze 3D Image Printing Using Artificial Intelligence in COVID-19
- The Evolution Of Emerging Market (EM) Sovereign CDSs Spreads During COVID-19
- Prediction of COVID-19 data using business intelligence tools
Lalitha S, Bhavana H T, K N Madhusudhan, Prascheth, Harshitha
M. Anantha Sunil, Sanjana T, Akshata Rai, Apoorva G Kanthi
Maligi Anantha Sunil, Sanjana T, Akhil S Raj, Abhishek A
Sreeja Sarasamma, Yashbir Singh
Pradeep Gangwar, Yashbir Singh and Vrijendra Singh
Paryati, Krit Salahddine
Nadir Oumayma, Daoui Driss
Sara EL HABBARI, Mhamed-Amine Soumiaa and Mohamed MANSOURI
Salah-ddine Krit is currently an Associate Professor at the Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University Agadir Morocco. Dr. Krit is currently The Director of Engineering Science and Energies Laboratory and The Chief of Department of Mathematics, Informatics and Management.
Vrijendra Singh is presently an Associate Professor & Head, at Department of Information Technology, Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa.
Mohamed Elhoseny is currently an Assistant Professor at the Faculty of Computers and Information, Mansoura University and a researcher at CoVIS Lab, Department of Computer Science and Engineering, University of North Texas. He also serves as the Director of Distributed Sensing and Intelligent Systems Lab, Mansoura University, Egypt.
Yashbir Singh is currently Medical Scientist at the Heart and Vascular Institute, WVU Medicine, USA.