Family farming is essentially characterized by the use of family labor force, due to the lack of land, water, and capital resources. An important tool is which allows them to know which products will be the best priced when production is completed, and at this point machine learning technology has, in particular, models and algorithms that allow for price prediction. The aim of this work is to review the literature related to price prediction of agricultural products using machine learning technology with the purpose of identifying the prediction models used in the studies. It also aims to identify the agricultural products used in these predictions to discuss their application in other products. The results show that neural network model is the most used in the selected studies.

To report the use of Ketoconazole as alternative treatment for Andean Cutaneous Leishmaniasis (ACL) in two high incidence zones in Amazonas Department. Methods: It was considered patients with confirmed diagnosis of ACL whom there were difficulties for the administration of Pentavalent Antimonials. It was not considered patients below 2 years old, pregnant or nursing woman and patients with wounds bigger than 5 cm. diameter. Patients above 12 years old received Ketoconazole 600 mg. daily for 28 days; patients below 12 years old received only 200 mg. It was made clinical follow-up weekly during the treatment. There were treated 2 patients above and 2 patients below 12 years old. The two younger and one of the older had not been received any previous medical treatment, the other one had been received two previous courses of Glucantime®. The treatment was successful in the 4 cases....