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Background Leishmaniasis, a disease caused by a protozoan, causes numerous deaths in humans each year. After malaria, leishmaniasis is known to be the deadliest parasitic disease globally. Direct visual detection of leishmania parasite through microscopy is the frequent method for diagnosis of this disease. However, this method is time-consuming and subject to errors. This study was aimed to develop an artificial intelligence-based algorithm for automatic diagnosis of leishmaniasis. Methods We used the Viola-Jones algorithm to develop a leishmania parasite detection system. The algorithm includes three procedures: feature extraction, integral image creation, and classification. Haar-like features are used as features. An integral image was used to represent an abstract of the image that significantly speeds up the algorithm. The adaBoost technique was used to select the discriminate features and to train the classifier. Results A 65% recall and 50% precision was concluded in the detection of macrophages infected with the leishmania parasite. Also, these numbers were 52% and 71%, respectively, related to amastigotes outside of macrophages. Conclusion The developed system is accurate, fast, easy to use, and cost-effective. Therefore, artificial intelligence might be used as an alternative for the current leishmanial diagnosis methods.

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Toxoplasmosis is a globally parasitic zoonotic disease transmitted by Toxoplasma gondii protozoa. This infection in its chronic form can cause a change in its host's specific behavior and is also associated with developing neuropsychological symptoms in humans. Changes in neurotransmitters' levels, especially dopamine, have been identified as a behavior change factor in the infected host. This study aimed to evaluate serum dopamine levels in acute murine toxoplasmosis. In this study, 50 mice infected with Toxoplasma were studied in 5 separate groups, and ten healthy mice were considered a control group. For five consecutive days after parasite injection, blood sampling and serum isolation were performed daily from one of the groups. Serum dopamine levels were measured by HPLC method. Statistical studies showed that serum dopamine on the first to the fourth day after parasite inoculation was the same as the control group, but the fifth day began to increase. The present study results indicate that dopamine production in mice infected with Toxoplasma gondii increases from day five after infection. This result suggests that in acute toxoplasmosis, dopamine production is low, and the trend of chronic disease increases dopamine production.