Poor adherence is a major barrier to the proper treatment of cutaneous leishmaniasis: A case-control field assessment in Iran.

Leishmaniasis is an overlooked, poverty-stricken, and complex disease with growing social and public health problems. In general, leishmaniasis is a curable disease; however, there is an expansion of unresponsive cases to treatment in cutaneous leishmaniasis (CL). One of the effective and ignored determinants in the treatment outcome of CL is poor treatment adherence (PTA).

Prediction of 6 months endoscopic third ventriculostomy success rate in patients with hydrocephalus using a multi-layer perceptron network.

Objective: Discrimination between patients most likely to benefit from endoscopic third ventriculostomy (ETV) and those at higher risk of failure is challenging. Compared to other standard models, we have tried to develop a prognostic multi-layer perceptron model based on potentially high-impact new variables for predicting the ETV success score (ETVSS).

Methods: Clinical and radiological data of 128 patients have been collected, and ETV outcomes were evaluated.

Gene selection using pyramid gravitational search algorithm.

Genetics play a prominent role in the development and progression of malignant neoplasms. Identification of the relevant genes is a high-dimensional data processing problem. Pyramid gravitational search algorithm (PGSA), a hybrid method in which the number of genes is cyclically reduced is proposed to conquer the curse of dimensionality.

A novel diagnostic and prognostic approach for unresponsive patients with anthroponotic cutaneous leishmaniasis using artificial neural networks.

Cutaneous leishmaniasis (CL) imposes a major health burden throughout the tropical and subtropical regions of the globe. Unresponsive cases are common phenomena occurred upon exposure to the standard drugs. Therefore, rapid detection, prognosis and classification of the disease are crucial for selecting the proper treatment modality.