Binary Cat Swarm Optimization Feature Selection and Machine Learning Based Ensemble for the Classification of the Daily Living Activities of the Elders

2022 ◽  
pp. 191-198
Author(s):  
Dorin Moldovan ◽  
Ionut Anghel ◽  
Tudor Cioara ◽  
Cristina Pop ◽  
Viorica Chifu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Daily Living ◽  
Swarm Optimization ◽  
Daily Living Activities ◽  
Cat Swarm Optimization

scholarly journals Machine learning methods for detecting urinary tract infection and analysing daily living activities in people with dementia

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0209909 ◽  
Author(s):  
Shirin Enshaeifar ◽  
Ahmed Zoha ◽  
Severin Skillman ◽  
Andreas Markides ◽  
Sahr Thomas Acton ◽  
...  
Keyword(s):  
Machine Learning ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Daily Living ◽  
Learning Methods ◽  
Daily Living Activities ◽  
Machine Learning Methods ◽  
People With Dementia

scholarly journals Classification of Diabetes using Random Forest with Feature Selection Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 1295-1300 ◽  
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Random Forest ◽  
Electronic Health Records ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Health Records

Diabetes has become a serious problem now a day. So there is a need to take serious precautions to eradicate this. To eradicate, we should know the level of occurrence. In this project we predict the level of occurrence of diabetes. We predict the level of occurrence of diabetes using Random Forest, a Machine Learning Algorithm. Using the patient’s Electronic Health Records (EHR) we can build accurate models that predict the presence of diabetes.

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