Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis, 1st ed. 2022
Coordonnateurs : Pani Subhendu Kumar, Dash Sujata, dos Santos Wellington P., Chan Bukhari Syed Ahmad, Flammini Francesco
This book comprehensively covers the topic of COVID-19 and other pandemics and epidemics data analytics using computational modelling. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care. The new era of pandemics and epidemics bring tremendous opportunities and challenges due to the plentiful and easily available medical data allowing for further analysis. The aim of pandemics and epidemics research is to ensure high-quality, efficient healthcare, better treatment and quality of life by efficiently analyzing the abundant medical, and healthcare data including patient?s data, electronic health records (EHRs) and lifestyle. In the past, it was a common requirement to have domain experts for developing models for biomedical or healthcare. However, recent advances in representation learning algorithms allow us to automatically learn the pattern and representation of the given data for the development of such models. Medical Image Mining, a novel research area (due to its large amount of medical images) are increasingly generated and stored digitally. These images are mainly in the form of: computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients? biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions related to health care. Image mining in medicine can help to uncover new relationships between data and reveal new and useful information that can be helpful for scientists and biomedical practitioners.
Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis will play a vital role in improving human life in response to pandemics and epidemics. The state-of-the-art approaches for data mining-based medical and health related applications will be of great value to researchers and practitioners working in biomedical, health informatics, and artificial intelligence..
Pramit Pandit , K. N. Krishnamurthy and Bishvajit Bakshi
Chapter 2: COVID-19 TravelCover: Post-lockdown Smart Transportation Management System for COVID-19
Sandeep Tiwari, Hari Mohan Rai, Barnini Goswami , Shreya Majumdar, Kajal Gupta
Chapter 3: Diverse techniques applied for effective diagnosis of COVID 19
Charles Oluwaseun Adetunji, Olugbemi Tope Olaniyan, Olulope Olufemi Ajayi, Osikemekha Anthony Anani, Ruth Ebunoluwa Bodunrinde, Abel Inobeme
Chapter 4: A Review on Detection of Covid-19 Patients using Deep Learning Techniques
Babita Majhi , Rahul Thangeda , Ritanjali Majhi
Chapter 5: Internet of Health Things (IoHT) for COVID 19
Charles Oluwaseun Adetunji, Olugbemi Tope Olaniyan, Olulope Olufemi Ajayi, Osikemekha Anthony Anani, Ruth Ebunoluwa Bodunrinde, Abel Inobeme
Chapter 6: Diagnosis for COVID-19
Ashish Tripathi , Anand Bhushan Pandey , Arun Kumar Singh , K. K. Mishra , Prem Chand Vashist
Chapter 7:IoT in Combating Covid 19 Pandemics: Lessons for Developing Countries
Oyekola Peter, Suchismita Swain, Kamalakanta Muduli, Adimuthu Ramasamy
Chapter 8: Machine learning approaches for COVID 19 pandemic
Charles Oluwaseun Adetunji, Olugbemi Tope Olaniyan, Olulope Olufemi Ajayi,Osikemekha Anthony Anani, Ruth Ebunoluwa Bodunrinde, Abel Inobeme
Chapter 9: Smart sensing for COVID 19 Pandemic
Charles Oluwaseun Adetunji, Olugbemi Tope Olaniyan, Olulope Olufemi Ajayi, Osikemekha Anthony Anani, Ruth Ebunoluwa Bodunrinde, Abel Inobeme
Chapter 10: eHealth, mHealth and Telemedicine for COVID-19 pandemic
Charles Oluwaseun Adetunji, Olugbemi Tope Olaniyan, Olulope Olufemi Ajayi, Osikemekha Anthony Anani, Ruth Ebunoluwa Bodunrinde, Abel Inobeme
Chapter 11: Prediction of care for patients in a Covid-19 pandemic situation based on haematological parameters
Arianne Sarmento Torcate , Flávio Secco Fonseca , Antônio Ravely. T. Lima , Flaviano Palmeira Santos , Tássia D. Muniz S. Oliveira , Maíra Araújo de Santana , Juliana Carneiro Gomes , Clarisse Lins de Lima , Valter Augusto de Freitas Barbosa , Ricardo Emmanuel de Souza , Wellington Pinheiro dos Santos
Chapter 12: Bioinformatics in Diagnosis of Covid-19
Sanjana Sharma, Saanya Aroura, Archana Gupta, Anjali Priyadarshini
Chapter 13: Predicting the Covid-19 Morbidity Outspread and Mortality Using Deep Learning Techniques
Bhimavarapu Usharani
Chapter 14: LSTM -CNN Deep learning Based Hybrid system for real time COVID-19 data analysis and prediction using Twitter data
Sitanath Biswas, Sujata Dash
Chapter 15: An intelligent tool to support diagnosis of Covid-19 by texture analysis of computerized tomography x-ray images and machine learning
Maíra Araújo de Santana , Juliana Carneiro Gomes , Valter Augusto de Freitas Barbosa , Clarisse Lins de Lima , Jonathan Bandeira , Mêuser Jorge Silva Valença , Ricardo Emmanuel de Souza, Aras Ismael Masood , Wellington Pinheiro dos Santos
Chapter 16: Analysis of Blockchain Backed Covid19 Data
Tadepalli Sarada Kiranmayee, Ruppa K. Thulasiram
Chapter 17:Intelligent systems for dengue, chikungunya and zika temporal and spatio-temporal forecasting: a contribution and a brief review
Clarisse Lins de Lima , Ana Clara Gomes da Silva , Cecilia Cordeiro da Silva , Giselle Machado Magalhães Moreno , Abel Guilhermino da Silva Filho , Anwar Musah , Aisha Aldosery , Livia Dutra , Tercio Ambrizzi , Iuri Valério Graciano Borges , Merve Tunali ,Selma Basibuyuk , Orhan Yenigün , Tiago Lima Massoni , Kate Jones , Luiza Campos , Patty Kostkova , Wellington Pinheiro dos Santos
Chapter 18: Machine learning approaches for temporal and spatio-temporal Covid-19 forecasting: a brief review and a contribution
Ana Clara Gomes da Silva , Clarisse Lins de Lima , Cecilia Cordeiro da Silva , Giselle Machado Magalhães Moreno , Eduardo Luiz Silva , Gabriel Souza Marques , Lucas Job Brito de Araújo , Luiz Antônio Albuquerque Júnior , Samuel Barbosa Jatobá de Souza , Maíra Araújo de Santana , Juliana Carneiro Gomes , Valter Augusto de Freitas Barbosa , Anwar Musah , Patty Kostkova , Abel Guilhermino da Silva Filho , Wellington Pinheiro dos Santos
Chapter 19: Image Reconstruction for COVID-19 using Multi-frequency Electrical Impedance Tomography
Julia Grasiela Busarello Wolff, David William Cordeiro Marcondes, Wellington Pinheiro dos Santos, Pedro Bertemes-Filho
Sujata Dash is Associate Professor of Computer Science at North Orissa University in the Department of Computer Application, Baripada, India. She is a recipient of Titular Fellowship from Association of Commonwealth Universities, UK. She has worked as a visiting professor of Computer Science Department of University of Manitoba, Canada. She has published more than 170 technical papers.
Wellington P. dos Santos is Associate Professor, Department of Biomedical Engineering, Federal University of Pernambuco (UFPE), Recife, Brazil. PhD in Electrical Engineering from the Federal University of Campina Grande (UFCG), Campina Grande, Master in Electrical Engineering and Graduated in Electronic Electrical Engineering from UFPE, Recife, Brazil. His main research interests are: diagnostic support systems, digital epidemiology, applied neuroscience, serious games in health, and artificial intelligence applied to health.
Syed Ahmad Chan Bukhari is Assistant Professor and Director of Healthcare Informatics at St. John's University, New York. He received his Ph.D. in Computer Science from the University of New Brunswick, Canada, and then went on to complete his postdoctoral fellowship at Yale School of Medicine, where he worked with Stanford University, Centre of Expanded Data Annotation and Retrieval (CEDAR) to develop data submission pipelines to improve scientific experimental reproducibility.
Francesco Flammini is Professor of Comp
Presents innovative solutions utilizing informatics to deal with various issues related to the COVID-19 outbreaks, including health data analytics, information exchange, knowledge sharing, Internet of Things (IoT)-based solutions, and the implementation, assessment, adoption, and management of healthcare informatics solutions
Reveals recent findings and results concerning a wide variety of COVID-19 and other pandemics and epidemics using Computational Modelling and Data Analysis
Beneficial for new researchers and practitioners working in the field to quickly know the best performing methods. Enables the comparison of different approaches in forwarding research in this important area directly impacting human life and health
Date de parution : 12-2022
Ouvrage de 405 p.
15.5x23.5 cm
Date de parution : 12-2021
Ouvrage de 405 p.
15.5x23.5 cm
