Malaria patients in Nigeria: Data exploration approach

Adeboye, Nureni Olawale; Abimbola, Olawale Victor; Folorunso, Sakinat Oluwabukonla

doi:10.1016/j.dib.2019.104997

Cited by 9 publications

(6 citation statements)

References 7 publications

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“…The dataset used in this study are data of malaria patient in Nigeria [14]. The data is in csv form.…”

Section: Methodsmentioning

confidence: 99%

Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes

Irmanita

2021

RESTI

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Malaria is a disease caused by the Plasmodium parasite that transmitted by female Anopheles mosquitoes. Malaria can become a dangerous disease if late have the medical treatment. The late medical treatment happened because of misdiagnosis and lack of medical staff, especially in the countryside. This problem can cause severe malaria that has complications. This study creates a system prediction to classify the severe malaria disease using Classification and Regression Tree (CART) method and the probability of malaria complication using Naïve Bayes method. The first step of this study is classifying the patients that have symptom are infected severe malaria or not based on the model that has been built. The next step, if the patient classified severe malaria then the data predicted if there any probability of complication by the malaria. There are 8 possibilities of complication malaria which are convulsion, hypoglycemia, hyperpyrexia, and the combinations of these four. The first step will evaluate by using F-score, precision and recall while the second step will evaluate by using accuracy. The highest result F-score, precision and recall are 0.551, 0.471 and 0.717. The highest accuracy 81.2% which predicted the complication is Hypoglycemia.

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“…The dataset used in this study are data of malaria patient in Nigeria [14]. The data is in csv form.…”

Section: Methodsmentioning

confidence: 99%

Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes

Irmanita

2021

RESTI

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“…Here are some preventive actions you may take to keep malaria at bay and prevent it from spreading faster [43,44]. Use insect repellent on any exposed skin [45,46]. The repellent advised comprises 20-35% N,N-Diethyl-meta-toluamide (DEET).…”

Section: Preventionmentioning

confidence: 99%

A Systematic Review on Malaria Disease and Its Treatments Focus on Artemether Drug

PHALAK,

BODKE,

BODKE

et al. 2024

Int J Curr Pharm Sci

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Malaria is one of the infectious illnesses of the highest scientific significance and importance to international health organizations. Plasmodium falciparum, the parasite responsible for a highly severe form of the disease in Africa, has traditionally received the most attention. However, in the last two decades, the Plasmodium vivax parasite, which is linked to a large number of cases in Latin America, the Middle East, South and Southeast Asia, the Horn of Africa, and Oceania, has sparked enormous interest, owing to published evidence that it can cause severe malaria, among other things. Malaria is a worldwide public health problem, with a saw 247 million cases recorded in 2021. African countries accounted for approximately 94% of all reported cases. So far, over 200 distinct varieties of protozoa have been discovered and identified, with at least 13 of them being pathogenic to humans. The malaria parasite's life cycle is a complex process involving a mosquito with the species Anopheles and a vertebrate host. Artemether is a lipid-soluble artemisinin derivative. It is available in both oral and intramuscular forms. It is also available as a fixed-dose formulation with lumefantrine. Artemether-lumefantrine is one of the ACTs authorized by the WHO and is being used by the majority of countries transitioning from less effective medications to ACTs. However, the emergence of antimalarial medication resistance poses a significant challenge to malaria control. It works by killing the pathogenic organisms responsible for malaria. It is known as an antimalarial medication, and it is more effective than quinine therapies.

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“…Specifically, most of these current clinical research studies investigated the factors responsible for malaria transmission using human subject reference data ( Achieng et al ., 2020 ; Anokye et al ., 2018 ; Esayas et al ., 2020 ). Several statistical and mathematical models have been useful in investigating these factors ( Adeboye et al ., 2020 ; Adegbite et al., 2022 ; Alegana et al ., 2020 ; Li & Liu, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling of malaria transmission dynamics in humans with mobility and control states

Adegbite,

Edeki,

Isewon

et al. 2023

Infectious Disease Modelling

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Malaria patients in Nigeria: Data exploration approach

Cited by 9 publications

References 7 publications

Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes

Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes

A Systematic Review on Malaria Disease and Its Treatments Focus on Artemether Drug

Mathematical modeling of malaria transmission dynamics in humans with mobility and control states

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