Intelligent computing applications for COVID-19 : (Record no. 71371)

000 -LEADER
fixed length control field 05207cam a2200565 i 4500
001 - CONTROL NUMBER
control field 9781003141105
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711212458.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210501t20212021flua ob 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781003141105
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1003141102
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781000423631
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1000423638
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781000423600
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1000423603
-- electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- hardcover
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- paperback
082 00 - CLASSIFICATION NUMBER
Call Number 614.5/924140285
245 00 - TITLE STATEMENT
Title Intelligent computing applications for COVID-19 :
Sub Title predictions, diagnosis, and prevention /
250 ## - EDITION STATEMENT
Edition statement First edition.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (xv, 305 pages) :
490 0# - SERIES STATEMENT
Series statement Innovations in health informatics and healthcare : using artificial intelligence and smart computing
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Deep learning for COVID-19 infection's diagnosis, prevention and treatment / Amjad Rehman, Kashif Mehmood, Noor Ayesha -- Artificial intelligence in coronavirus detection -- recent findings and future perspectives / Syed Ale Hassan, Sahar Gull, Shahzad Akbar, Israr Hanif, Sajid Iqbal, Muhammad Waqas Aziz -- Solutions of differential equations for prediction of COVID-19 cases by homotopy perturbation method / Nahid Fatima and Monika Dhariwal -- Predictive models of hospital readmission rate using the improved AdaBoost in COVID 19 / Arash Raftarai, Rahemeh Ramazani Mahounaki , Majid Harouni, Mohsen Karimi, Shakiba Khadem Olghoran -- Nigerian Medical Laboratory diagnosis of COVID-19; from grass to grace / Obeta M. Uchejeso, Nkereuwem S. Etukudoh, Okoli C. Chukwudimma -- COVID-19 CT image segmentation and detection : review / Zahra Nourbakhsh -- Interactive medical chatbot for assisting COVID related queries / Aayush Gadia, Palash Nandi, Dipankar Das -- COVID-19 outbreak prediction after lockdown over based on current data analytics / Muhammad Kashif, Tariq Sadad, Zahid Mehmood -- A deep learning CNN model for genome sequence classification / Hemalatha Gunasekaran, K. Ramalakshmi, Shalini Ramanathan, R.Venkatesan -- The impact of lockdown strategies on COVID-19 cases with a confined sentiment analysis of COVID -19 tweets / Tanzila Saba, Hind Alaskar, Dalyah Ajmal, Erum Afzal -- A mathematical model and forecasting of nCovid19 : outbreak in India / G. Maria Jones, S. Godfrey Winster, A. George Maria Selvam and D. Vignesh -- Automatic lung infection segmentation of Covid-19 in CT scan images / Mohsen Karimi, Majid Harouni, Afrooz Nasr, Nakisa Tavakoli -- A review of feature selection algorithms in determining the factors affecting COVID-19 / Shadi Rafieipour, Sogand B Jaferi, Ziafat Rahmati, Nakisa Tavakoli, Shima Zarrabi Baboldasht -- Industry 4.0 technologies based diagnosis for COVID-19 / Manmeet Kaur, Mohan Singh, Jaskanwar Singh.
520 ## - SUMMARY, ETC.
Summary, etc "Accurate estimation, diagnosis, and prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI, and Mathematical Modeling applications. This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry. This book covers the state-of-the-art applications of AI and Machine Learning in past epidemics, pandemics, and COVID-19. It offers recent global case studies, and discusses how AI and statistical methods, initiatives, and applications such as Machine Learning, Deep Learning, Correlation and Regression Analysis play a major role in the prediction, diagnosis, and prevention of a pandemic. It will also focus on how AI and statistical applications can facilitate and restructure the healthcare system. This book is written for Researchers, Students, Professionals, Executives, and the general public"--
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Epidemiology
-- Data processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Epidemiology
-- Simulation methods.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Diagnosis
-- Data processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Diagnosis
-- Simulation methods.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Medical applications.
700 1# - AUTHOR 2
Author 2 Saba, Tanzila,
700 1# - AUTHOR 2
Author 2 Khan, AR
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.taylorfrancis.com/books/9781003141105
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Boca Raton, FL :
-- CRC Press,
-- 2021.
264 #4 -
-- ©2021
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
520 ## - SUMMARY, ETC.
-- Provided by publisher.
588 ## -
-- OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- COVID-19 (Disease)
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- COVID-19 (Disease)
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- COVID-19 (Disease)
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- COVID-19 (Disease)
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- TECHNOLOGY / Operations Research

No items available.