Predicting Semen Analysis Parameters from Testicular Ultrasonography Images Using Deep Learning Algorithms: An Innovative Approach to Male Infertility Diagnosis.

Semen analysis is universally regarded as the gold standard for diagnosing male infertility, while ultrasonography plays a vital role as a complementary diagnostic tool. This study aims to assess the effectiveness of artificial intelligence (AI)-driven deep learning algorithms in predicting semen analysis parameters based on testicular ultrasonography images. This study included male patients aged 18-54 who sought evaluation for infertility at the Urology Outpatient Clinic of our hospital between February 2022 and April 2023.

Generative Adversarial Network Based Contrast Enhancement: Synthetic Contrast Brain Magnetic Resonance Imaging.

Rationale And Objectives: Magnetic resonance imaging (MRI) is a vital tool for diagnosing neurological disorders, frequently utilising gadolinium-based contrast agents (GBCAs) to enhance resolution and specificity. However, GBCAs present certain risks, including side effects, increased costs, and repeated exposure. This study proposes an innovative approach using generative adversarial networks (GANs) for virtual contrast enhancement in brain MRI, with the aim of reducing or eliminating GBCAs, minimising associated risks, and enhancing imaging efficiency while preserving diagnostic quality.

Long term outcomes from the early days of minimally invasive thymoma surgery for Myasthenia Gravis patients: a follow-up of 19 years.

Background: Long-term survival outcomes are crucial for accurately determining the effectiveness of treatment in an indolent disease like thymoma. We aimed to analyze the clinical findings in terms of survival and relapse patterns with a median follow up of 105 months (8.7 years) in patients with thymoma and myasthenia gravis who underwent minimally invasive surgery between 2002 and 2015.

Accuracy and Readability of ChatGPT on Potential Complications of Interventional Radiology Procedures: AI-Powered Patient Interviewing.

Rationale And Objectives: It is crucial to inform the patient about potential complications and obtain consent before interventional radiology procedures. In this study, we investigated the accuracy, reliability, and readability of the information provided by ChatGPT-4 about potential complications of interventional radiology procedures.

Materials And Methods: Potential major and minor complications of 25 different interventional radiology procedures (8 non-vascular, 17 vascular) were asked to ChatGPT-4 chatbot.