Artificial Intelligence-Based Detection and Numbering of Dental Implants on Panoramic Radiographs.

Objectives: This study aimed to develop an artificial intelligence (AI)-based deep learning model for the detection and numbering of dental implants in panoramic radiographs. The novelty of this model lies in its ability to both detect and number implants, offering improvements in clinical decision support for dental implantology.

Materials And Methods: A retrospective dataset of 32 585 panoramic radiographs, collected from patients at Sivas Cumhuriyet University between 2014 and 2024, was utilized.

Bone Mineral Density Improvement After Resolution of Endogenous Cushing Syndrome: A Systematic Review and Meta-Analysis.

Objective: We aimed to identify all evidence to evaluate bone mineral density (BMD) improvement after resolution of endogenous Cushing syndrome (eCS).

Methods: Potentially eligible studies were identified from the EMBASE and PubMed databases from inception to February 2024, utilizing a search strategy incorporating terms related to "Bone mineral density" and "Cushing syndrome". Eligible studies must include patients diagnosed with eCS.

Impairments of attention in RRMS patients: the role of disease duration.

Introduction: The extent to which different types of attention are affected in RRMS based on disease duration has not been extensively analyzed. Therefore, the aim of this study was to determine whether MS patients differ compared to healthy individuals in a homogeneous sample of RRMS patients in terms of attention types and from which year of MS attention deficit starts. Another aim of the study was to examine the effect of MS duration and stimulus onset asynchrony on dual task performance.

Computational Fluid Dynamics of Cerebrospinal Fluid.

Cerebrospinal fluid (CSF) plays a critical role in the healthy function of the brain, yet the mechanics of CSF flow remain poorly understood. Computational fluid dynamics is a powerful tool capable of resolving the spatiotemporal evolution of CSF pressures and velocities, but technical and methodological limitations have limited the clinical use of CFD to date. With improvements in medical imaging, computational power, and machine learning, however, CFD may be on the cusp of breaking through into the medical mainstream.