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Detection of Infectious Disease using Non-Invasive Logistic Regression Technique
2019
2019 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS)
The detection of infectious disease like Malaria among humans has been a challenging task for a long time. Although it is not life-threatening, if timely care is not provided to the individual, it may lead to serious health consequences. It has been realized that certain individualistic parameters like blood sugar, heart rate and body temperature are indicators of occurrence of malaria in a person. The objective of the work is to develop a logistic regression model for prediction of malaria
doi:10.1109/incos45849.2019.8951392
fatcat:bzrfa7ymevc37hqlua65jp75mi