Ramadan diurnal intermittent fasting in patients with diabetes: assessment of knowledge, practices, risk of complications, and impact of pre-ramadan education.

Objectives: Evaluate diabetic patients' knowledge, practices, and the prevalence of complications during Ramadan fasting (RF) before and after an education program.

Methods: We conducted a prospective study including 140 consecutive diabetic patients (DP) who intended to observe RF in 2023. Patients underwent a questionnaire and received pre-Ramadan education (PRE) according to the IDF-DAR 2021 recommendations.

Optimization of convolutional neural network and visual geometry group-16 using genetic algorithms for pneumonia detection.

Pneumonia is still a major global health issue, so effective diagnostic methods are needed. This research proposes a new methodology for improving convolutional neural networks (CNNs) and the Visual Geometry Group-16 (VGG16) model by incorporating genetic algorithms (GAs) to detect pneumonia. The work uses a dataset of 5,856 frontal chest radiography images critical in training and testing machine learning algorithms.

International consensus on fasting terminology.

Although fasting is increasingly applied for disease prevention and treatment, consensus on terminology is lacking. Using Delphi methodology, an international, multidisciplinary panel of researchers and clinicians standardized definitions of various fasting approaches in humans. Five online surveys and a live online conference were conducted with 38 experts, 25 of whom completed all 5 surveys.