Classification of H. pylori Infection from Histopathological Images Using Deep Learning.

Helicobacter pylori (H. pylori) is a widespread pathogenic bacterium, impacting over 4 billion individuals globally. It is primarily linked to gastric diseases, including gastritis, peptic ulcers, and cancer.

Assessment of Deep Learning Models for Cutaneous Leishmania Parasite Diagnosis Using Microscopic Images.

Cutaneous leishmaniasis (CL) is a common illness that causes skin lesions, principally ulcerations, on exposed regions of the body. Although neglected tropical diseases (NTDs) are typically found in tropical areas, they have recently become more common along Africa's northern coast, particularly in Libya. The devastation of healthcare infrastructure during the 2011 war and the following conflicts, as well as governmental apathy, may be causal factors associated with this catastrophic event.

Effective deep learning classification for kidney stone using axial computed tomography (CT) images.

Introduction: Stone formation in the kidneys is a common disease, and the high rate of recurrence and morbidity of the disease worries all patients with kidney stones. There are many imaging options for diagnosing and managing kidney stone disease, and CT imaging is the preferred method.

Objectives: Radiologists need to manually analyse large numbers of CT slices to diagnose kidney stones, and this process is laborious and time-consuming.

Recreational tobacco consumption and food insecurity among First Nations in Canada.

Objective: Crowding-out effects of tobacco consumption refers to the situation in which tobacco consumption reduces a household's spending on other commodities. In this paper, we test for the crowding-out effects of recreational tobacco consumption on food expenditures among on-reserve Indigenous communities in Canada.

Methods: We use data from household expenditure surveys (N=469) to investigate tobacco consumption behaviour of on-reserve households of six First Nation communities in Canada.