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Computer Aided Malaria Disease Prediction System for Doctor and Patient Interaction


Affiliations
1 Department of Computer Science, Afe Babalola University, Ado-Ekiti, Nigeria
     

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It has been already observed that machine learning has revolutionized the field of computer vision. Hardly a few years ago, It has transformed this field into practically true, in-your-pocket technologies out of those technologies which were usually considered like science fiction. If nearly human-level accuracy can be achieved through modern computer vision system in identifying dog breeds or cars, why not the current disease diagnostic system might not be as much capable of learning to identify the disease (disease pre-screening) using medical data (medical images or biomedical signal)?. This system is useful to help doctors or users to diagnosis the disease of patient in a short time and effectively via the identified symptoms.  Mosquitoes are surviving on earth since millions of years. They have always given tough time to men as important carriers of various diseases. Malaria and dengue remains to be the most vital cause of morbidity and mortality in India and in many other tropical countries with complete 2 to 3 million new cases arising every year. Malaria is a major health problem in the world. Malaria is well-known oldest chronic and most widespread fatal disease that has plagued mankind for centuries, which also causes economical loss.

Keywords

Malaria, Machine Learning, Random Forest
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  • Computer Aided Malaria Disease Prediction System for Doctor and Patient Interaction

Abstract Views: 229  |  PDF Views: 1

Authors

Cecilia Di Ruberto
Department of Computer Science, Afe Babalola University, Ado-Ekiti, Nigeria
StefanJaeger
Department of Computer Science, Afe Babalola University, Ado-Ekiti, Nigeria

Abstract


It has been already observed that machine learning has revolutionized the field of computer vision. Hardly a few years ago, It has transformed this field into practically true, in-your-pocket technologies out of those technologies which were usually considered like science fiction. If nearly human-level accuracy can be achieved through modern computer vision system in identifying dog breeds or cars, why not the current disease diagnostic system might not be as much capable of learning to identify the disease (disease pre-screening) using medical data (medical images or biomedical signal)?. This system is useful to help doctors or users to diagnosis the disease of patient in a short time and effectively via the identified symptoms.  Mosquitoes are surviving on earth since millions of years. They have always given tough time to men as important carriers of various diseases. Malaria and dengue remains to be the most vital cause of morbidity and mortality in India and in many other tropical countries with complete 2 to 3 million new cases arising every year. Malaria is a major health problem in the world. Malaria is well-known oldest chronic and most widespread fatal disease that has plagued mankind for centuries, which also causes economical loss.

Keywords


Malaria, Machine Learning, Random Forest