Impact of Deep Learning-Based Image Reconstruction on Tumor Visibility and Diagnostic Confidence in Computed Tomography.

Deep learning image reconstruction (DLIR) has shown potential to enhance computed tomography (CT) image quality, but its impact on tumor visibility and adoption among radiologists with varying experience levels remains unclear. This study compared the performance of two deep learning-based image reconstruction methods, DLIR and Pixelshine, an adaptive statistical iterative reconstruction-volume (ASIR-V) method, and filtered back projection (FBP) across 33 contrast-enhanced CT staging examinations, evaluated by 20-24 radiologists. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured for tumor and surrounding organ tissues across DLIR (Low, Medium, High), Pixelshine (Soft, Ultrasoft), ASIR-V (30-100%), and FBP.

Evaluation of deep learning-based depression detection using medical claims data.

Human accuracy in diagnosing psychiatric disorders is still low. Even though digitizing health care leads to more and more data, the successful adoption of AI-based digital decision support (DDSS) is rare. One reason is that AI algorithms are often not evaluated based on large, real-world data.

Maxillary lateral incisor agenesis is associated with maxillary form: a geometric morphometric analysis.

Background And Objective: Agenesis of the maxillary lateral incisor occurs in up to 4% of all individuals and requires multidisciplinary treatment. Its developmental origins, however, are not fully understood. Earlier studies documented genetic factors contributing to agenesis but also an association with craniofacial morphology.

A systematic literature review of AI-based digital decision support systems for post-traumatic stress disorder.

Objective: Over the last decade, an increase in research on medical decision support systems has been observed. However, compared to other disciplines, decision support systems in mental health are still in the minority, especially for rare diseases like post-traumatic stress disorder (PTSD). We aim to provide a comprehensive analysis of state-of-the-art digital decision support systems (DDSSs) for PTSD.

Salivary MRP-8/14 and the presence of periodontitis-associated bacteria in children with bonded maxillary expansion treatment.

Objectives: The aim of this study was to investigate changes in saliva concentration of the inflammatory marker MRP-8/14 and the presence of some periodontitis-associated bacteria in patients with mixed dentition treated with a rigid acrylic, bonded maxillary expander.

Methods: Fifteen patients in mixed dentition treated with a bonded palatal expander were enrolled in this longitudinal study. Saliva samples were taken before the therapy, as well as in 2 weeks and 3, 6, 9, and 12 months after the beginning of the therapy.