Call for Special Issue Papers: Big Data Analytics for Agricultural Disaster Management

Big Data ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 450-451
Author(s):  
S. Balamurugan ◽  
Bala Anand Muthu ◽  
Sheng-Lung Peng ◽  
Mohd Helmy Abd Wahab
Big Data ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 544-545
Author(s):  
S. Balamurugan ◽  
Bala Anand Muthu ◽  
Sheng-Lung Peng ◽  
Mohd Helmy Abd Wahab

Big Data ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 87-88
Author(s):  
Priyan Malarvizhi Kumar ◽  
Hari Mohan Pandey ◽  
Gautam Srivastava

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 54595-54614 ◽  
Author(s):  
Syed Attique Shah ◽  
Dursun Zafer Seker ◽  
Sufian Hameed ◽  
Dirk Draheim

2018 ◽  
Vol 14 ◽  
pp. 55-56
Author(s):  
Kevin Kam Fung Yuen ◽  
Steven Sheng-Uei Guan ◽  
Kit Yan Chan ◽  
Vasile Palade

Author(s):  
Joice K. Joseph ◽  
Karunakaran Akhil Dev ◽  
A.P. Pradeepkumar ◽  
Mahesh Mohan

Big Data ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 146-147
Author(s):  
Ahmed A. Abd El-Latif ◽  
Lo'ai Tawalbeh ◽  
Yassine Maleh ◽  
Gokay Saldamli

Author(s):  
Chien-Lung Chan ◽  
Chi-Chang Chang

Unlike most daily decisions, medical decision making often has substantial consequences and trade-offs. Recently, big data analytics techniques such as statistical analysis, data mining, machine learning and deep learning can be applied to construct innovative decision models. With complex decision making, it can be difficult to comprehend and compare the benefits and risks of all available options to make a decision. For these reasons, this Special Issue focuses on the use of big data analytics and forms of public health decision making based on the decision model, spanning from theory to practice. A total of 64 submissions were carefully blind peer reviewed by at least two referees and, finally, 23 papers were selected for this Special Issue.


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