No abstract

Preeclampsia is one of the illnesses associated with placental dysfunction and pregnancy-induced hypertension, which appears after the first 20 weeks of pregnancy and is marked by proteinuria and hypertension. It can affect pregnant women and limit fetal growth, resulting in low birth weights, a risk factor for neonatal mortality. Approximately 10% of pregnancies worldwide are affected by hypertensive disorders during pregnancy. In this review, we discuss the machine learning and deep learning methods for preeclampsia prediction that were published between 2018 and 2022. Many models have been created using a variety of data types, including demographic and clinical data. We determined the techniques that successfully predicted preeclampsia. The methods that were used the most are random forest, support vector machine, and artificial neural network (ANN). In addition, the prospects and challenges in preeclampsia prediction are discussed to boost the research on artificial intelligence systems, allowing academics and practitioners to improve their methods and advance automated prediction.

Background and purpose: Magnetic Resonance Imaging (MRI) is increasingly being used in radiotherapy (RT). However, geometric distortions are a known challenge of using MRI in RT. The aim of this study was to demonstrate feasibility of a national audit of MRI geometric distortions. This was achieved by assessing large field of view (FOV) MRI distortions on a number of scanners used clinically for RT. Materials and methods: MRI scans of a large FOV MRI geometric distortion phantom were acquired on 11 MRI scanners that are used clinically for RT in the UK. The mean and maximum distortions and variance between scanners were reported at different distances from the isocentre. Results: For a small FOV representing a brain (100-150 mm from isocentre) all distortions were < 2 mm except for the maximum distortion of one scanner. For a large FOV representing a head and neck/pelvis (200-250 mm from isocentre) mean distortions were < 2 mm except for one scanner, maximum distortions were > 10 mm in some cases. The variance between scanners was low and was found to increase with distance from isocentre. Conclusions: This study demonstrated feasibility of the technique to be repeated in a country wide geometric distortion audit of all MRI scanners used clinically for RT. Recommendations were made for performing such an audit and how to derive acceptable limits of distortion in such an audit.

Considering the global trend to confine the COVID‐19 pandemic by applying various preventive health measures, preprocedural mouth rinsing has been proposed to mitigate the transmission risk of SARS‐CoV‐2 in dental clinics. The study aimed to investigate the effect of different mouth rinses on salivary viral load in COVID‐19 patients. This study was a single‐center, randomized, double‐blind, six‐parallel‐group, placebo‐controlled clinical trial that investigated the effect of four mouth rinses (1% povidone‐iodine, 1.5% hydrogen peroxide, 0.075% cetylpyridinium chloride, and 80 ppm hypochlorous acid) on salivary SARS‐CoV‐2 viral load relative to the distilled water and no‐rinse control groups. The viral load was measured by quantitative reverse transcription PCR (RT‐qPCR) at baseline and 5, 30, and 60 min post rinsing. The viral load pattern within each mouth rinse group showed a reduction overtime; however, this reduction was only statistically significant in the hydrogen peroxide group. Further, a significant reduction in the viral load was observed between povidone‐iodine, hydrogen peroxide, and cetylpyridinium chloride compared to the no‐rinse group at 60 min, indicating their late antiviral potential. Interestingly, a similar statistically significant reduction was also observed in the distilled water control group compared to the no‐rinse group at 60 min, proposing mechanical washing of the viral particles through the rinsing procedure. Therefore, results suggest using preprocedural mouth rinses, particularly hydrogen peroxide, as a risk‐mitigation step before dental procedures, along with strict adherence to other infection control measures.