Here, a machine learning tool (YOLOv5) enables the detection of microorganisms using optical and phase contrast microscope images. The two databases were processed using 520 images (optical microscopy) and 1200 images (phase contrast microscopy). It used Python libraries to label, standardize the size, and crop the images to generate the input tensors to the YOLOv5 network (s, m, and l).
View Article and Find Full Text PDFIntroduction: The Kaposi's sarcoma (KS) incidence has markedly changed in the general population since the onset of the AIDS epidemic in the eighties and after the introduction of the Highly Active Antiretroviral Therapy (HAART) in the nineties.
Objective: To investigate incidence rate trends for Kaposi's sarcoma before and during the (HIV/AIDS) epidemic in Cali, Colombia.
Methods: Exploratory ecological study that included all Kaposi's sarcoma cases identified by the Cali Cancer Registry from 1962-2007, and 12,887 cases of HIV/AIDS recorded in the Municipal Health Secretariat of Cali between 1986 and 2010.