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Reliability and quality of information provided by artificial intelligence chatbots on post-contrast acute kidney injury: an evaluation of diagnostic, preventive, and treatment guidance.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: The aim of this study was to evaluate the reliability and quality of information provided by artificial intelligence chatbots regarding the diagnosis, preventive methods, and treatment of contrast-associated acute kidney injury, while also...

Machine Learning Differentiates Between Benign and Malignant Parotid Tumors With Contrast-Enhanced Ultrasound Features.

Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
BACKGROUND: Contrast-enhanced ultrasound (CEUS) is frequently used to distinguish benign parotid tumors (BPTs) from malignant parotid tumors (MPTs). Introducing machine learning may enable clinicians to preoperatively diagnose parotid tumors precisel...

A CT-based deep learning for segmenting tumors and predicting microsatellite instability in patients with colorectal cancers: a multicenter cohort study.

La Radiologia medica
PURPOSE: To develop and validate deep learning (DL) models using preoperative contrast-enhanced CT images for tumor auto-segmentation and microsatellite instability (MSI) prediction in colorectal cancer (CRC).

Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning.

International journal of cardiology
BACKGROUND: Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial fibrosis and may lead to fatal ventricular arrhythmias. However, CMR is resource-intensive and some...

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

Academic radiology
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 risk...

Development and Validation of a Deep Learning System to Differentiate HER2-Zero, HER2-Low, and HER2-Positive Breast Cancer Based on Dynamic Contrast-Enhanced MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Previous studies explored MRI-based radiomic features for differentiating between human epidermal growth factor receptor 2 (HER2)-zero, HER2-low, and HER2-positive breast cancer, but deep learning's effectiveness is uncertain.

Deep Learning for Contrast Enhanced Mammography - A Systematic Review.

Academic radiology
BACKGROUND/AIM: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that enables both anatomical and functional breast imaging, with improved diagnostic performance compared to standard 2D mammography. The aim of this study is...