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RISK FACTOR IDENTIFICATION FOR STROKE PROGNOSIS USING MACHINE-LEARNING ALGORITHMS

(Received: 16-May-2022, Revised: 6-Jul.-2022 , Accepted: 7-Jul.-2022)
Tanvir Ahammad
#Stroke prediction #Machine learning #Classification #Feature selection #Stroke risk factors #Healthcare
  • Views: 4201
  • Downloads: 760
  • DOI: 10.5455/jjcit.71-1652725746
  • Cited by: 9
Abstract

DEVELOPMENT OF ENSEMBLE MACHINE LEARNING MODEL TO IMPROVE COVID-19 OUTBREAK FORECASTING

(Received: 22-Dec.-2021, Revised: 27-Feb.-2022 , Accepted: 25 -Mar.-2022 )
Meaad Alrehaili,Fatmah Assiri
#COVID-19 #Coronavirus disease #Coronavirus #Pandemic #Epidemic prediction #Future forecasting #Machine learning #Ensemble machine learning algorithms #Naive Bayes #Support vector machine #Random forest #Gradient boosting
  • Views: 2860
  • Downloads: 704
  • DOI: 10.5455/jjcit.71-1640174252
  • Cited by: 2
Abstract

PHIBOOST- A NOVEL PHISHING DETECTION MODEL USING ADAPTIVE BOOSTING APPROACH

(Received: 14-Sep.-2020, Revised: 6-Nov.-2020 , Accepted: 15-Dec.-2020)
Ammar Odeh,Ismail Keshta,Eman Abdelfattah
#Adaptive boost #Feature selection #Correlation-based feature #Machine learning
  • Views: 4401
  • Downloads: 1207
  • DOI: 10.5455/jjcit.71-1600061738
  • Cited by: 29
Abstract
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