Travel-associated malaria is a health hazard, even in non-malaria endemic regions. This is a hospital-based retrospective study of 12,931 febrile patients who presented at King Fahad Hospital of the University (KFHU) from January 2009 to December 2019. Patients either returning from malaria endemic countries and/or for whom malaria was suspected, had blood films microscopically screened for malaria parasites. Malaria prevalence was very low in febrile patients attending KFHU. Out of the 12,931 febrile patients, 0.63% (n = 81) were malaria positive, all travel-related, except for one case of transfusion malaria. Indian nationals were the most infected (29.6%, n = 24), followed by Sudanese nationals (24.7%, n = 20). P. falciparum (47%, n = 38) and P. vivax (42%, n = 24) were the predominant species. The majority of P. falciparum (64.5%, n = 20) cases were from African nationals and the majority of P. vivax (72.7%, n = 24) cases were from Asia. The highest percentage of malaria patients were adult (90%, n = 73), males (85.2%, n = 69), ages ranged from 6 to 65, with a mean of 34.6 years. Most of the malaria cases presented at the emergency room (ER), only 3 required critical care. Only sex, hospitalized in-patient (IP) and attendance at ER were statistically associated with malaria. In the presence of a potential vector, travel-associated malaria in non-malaria endemic areas should be monitored to guide control strategies.Author summary: Malaria is a neglected potentially fatal tropical mosquito-born disease. Travel-associated malaria is a health hazard, even in non-malaria endemic regions. In spite of previous efforts to estimate malaria prevalence, morbidity and mortality in Saudi Arabia in the last decade, there have been no studies that determine the prevalence of malaria in Al-Khobar, Eastern Province of Saudi Arabia. Malaria prevalence was very low in febrile patients (81/12,931) attending King Fahad Hospital of the University over a decade. Cases were all travel-related, except for one case of transfusion malaria. Indian nationals were the most infected (29.6%), followed by Sudanese nationals (24.7%). P. falciparum (47%) and P. vivax (42%) were the predominant species. The majority of P. falciparum (64.5%) cases were from Africa and the majority of P. vivax (72.7%) cases were from Asia. No patient factors predicted malaria in febrile travelers. In non-malaria endemic areas, in the presence of a potential vector, patients with acute fever coming from endemic areas or having received blood transfusion, should be screened for travel-associated malaria to guide control strategies.
Heart diseases are considered one of the leading causes of death globally over the world. They are difficult to be predicted by a specialist physician as it is not an easy task which requires greater knowledge and expertise for prediction. With the variety of machine learning and deep learning algorithms, there exist many recent studies in the state of the art that have been done remarkable and practical works for predicting the presence of heart diseases. However, some of these works were affected by various drawbacks. Hence, this work aims to compare and analyze different classifiers, pre-processing, and dimensionality reduction techniques (feature selection and feature extraction) and study their effect on the prediction of heart diseases existence. Therefore, based on the resulting performance of several conducted experiments on the well-known Cleveland heart disease dataset, the findings of this study are: 1) the most significant subset of features to predict the existence of heart diseases are PES, EIA, CPT, MHR, THA, VCA, and OPK, 2) Naïve Bayes classifier gave the best performance prediction, and 3) Chi-squared feature selection was the data mining technique that reduced the number of features while maintained the same improved performance for predicting the presence of heart disease.
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