The relationship of compliance with immediate and delayed suggestibility and types of resistant behavioral responses in children aged 10-15 years.

This study examined the relationship of compliance with immediate and delayed suggestibility and types of resistant behavioral responses (RBRs) in 454 children (10-15 years) using the Gudjonsson Suggestibility Scale (GSS 2) and a slightly adapted version of the Gudjonsson Compliance Scale (GCS). The GCS was found to have satisfactory internal consistency with this age group. Immediate suggestibility and delayed suggestibility were significantly correlated (small effect size).

Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review.

The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound imaging in gynecology oncology. Web of Science, PubMed, and Scopus databases were searched. All studies were imported to RAYYAN QCRI software.

Radiomics analysis of ultrasound images to discriminate between benign and malignant adnexal masses with solid ultrasound morphology.

Objective: Our primary aim was to identify radiomic ultrasound features that can distinguish benign from malignant adnexal masses with solid ultrasound morphology, and primary invasive from metastatic solid ovarian masses, and to develop ultrasound-based machine learning models that include radiomics features to discriminate between benign and malignant solid adnexal masses. Our secondary aim was to compare the diagnostic performance of our radiomics models with that of the ADNEX model and subjective assessment by an experienced ultrasound examiner.

Methods: This is a retrospective observational single center study.

Impact of bias field correction on 0.35 T pelvic MR images: evaluation on generative adversarial network-based OARs' auto-segmentation and visual grading assessment.

Purpose: Magnetic resonance imaging (MRI)-guided radiotherapy enables adaptive treatment plans based on daily anatomical changes and accurate organ visualization. However, the bias field artifact can compromise image quality, affecting diagnostic accuracy and quantitative analyses. This study aims to assess the impact of bias field correction on 0.