Hybrid closed-loop systems for managing blood glucose levels in type 1 diabetes: a systematic review and economic modelling.

Background: Hybrid closed-loop systems are a new class of technology to manage type 1 diabetes mellitus. The system includes a combination of real-time continuous glucose monitoring from a continuous glucose monitoring device and a control algorithm to direct insulin delivery through an insulin pump. Evidence suggests that such technologies have the potential to improve the lives of people with type 1 diabetes mellitus and their families.

Software using artificial intelligence for nodule and cancer detection in CT lung cancer screening: systematic review of test accuracy studies.

Objectives: To examine the accuracy and impact of artificial intelligence (AI) software assistance in lung cancer screening using CT.

Methods: A systematic review of CE-marked, AI-based software for automated detection and analysis of nodules in CT lung cancer screening was conducted. Multiple databases including Medline, Embase and Cochrane CENTRAL were searched from 2012 to March 2023.

Artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer: an evidence synthesis early value assessment.

Background: Lung cancer is one of the most common types of cancer in the United Kingdom. It is often diagnosed late. The 5-year survival rate for lung cancer is below 10%.

Psychological wellbeing in parents of children with Down syndrome: A systematic review and meta-analysis.

We report a review examining the psychological wellbeing of parents of children with Down syndrome (DS) relative to that of parents of typically developing (TD) children. A systematic search identified 57 relevant studies, which were synthesised meta-analytically. Relative to their counterparts with TD children, mothers and fathers of children with DS reported higher levels of parenting stress (mothers: g = 0.

Fatigue and vigilance in medical experts detecting breast cancer.

An abundance of laboratory-based experiments has described a vigilance decrement of reducing accuracy to detect targets with time on task, but there are few real-world studies, none of which have previously controlled the environment to control for bias. We describe accuracy in clinical practice for 360 experts who examined >1 million women's mammograms for signs of cancer, whilst controlling for potential biases. The vigilance decrement pattern was not observed.