The role of interleukin-17 and interleukin-23 inhibitors in the development, progression, and recurrence of cancer: A systematic review.

Background: Biologicals targeting interleukin (IL)-17 and IL-23 improve quality of life in psoriasis and other chronic autoimmune disorders with a favorable safety profile. However, current guidelines do not recommend their use in patients with recent oncologic history due to limited evidence.

Objective: To understand the impact of IL-17 and IL-23 inhibitors on cancer development, progression, and recurrence by systematically reviewing available literature.

LUNet: deep learning for the segmentation of arterioles and venules in high resolution fundus images.

This study aims to automate the segmentation of retinal arterioles and venules (A/V) from digital fundus images (DFI), as changes in the spatial distribution of retinal microvasculature are indicative of cardiovascular diseases, positioning the eyes as windows to cardiovascular health.We utilized active learning to create a new DFI dataset with 240 crowd-sourced manual A/V segmentations performed by 15 medical students and reviewed by an ophthalmologist. We then developed LUNet, a novel deep learning architecture optimized for high-resolution A/V segmentation.