OBJECTIVES: To evaluate the use of a commercial artificial intelligence (AI)-based mammography analysis software for improving the interpretations of breast ultrasound (US)-detected lesions.
OBJECTIVES: The preoperative classification of pleomorphic adenomas (PMA) and Warthin tumors (WT) in the parotid gland plays an essential role in determining therapeutic strategies. This study aims to develop and validate an ultrasound-based ensemble...
PURPOSE: This study aims to develop a deep learning-based computer-aided diagnosis (CAD) system for the automatic detection and classification of lateral cervical lymph nodes (LNs) on original ultrasound images of papillary thyroid carcinoma (PTC) pa...
The use of machine learning techniques to identify problem gamblers has been widely established. However, existing methods often rely on self-reported labeling, such as temporary self-exclusion or account closure. In this study, we propose a novel ap...
BACKGROUND: PM is a harmful mixture of various chemical components that pose a challenge in determining their individual and combined health effects due to multicollinearity issues with traditional linear regression models. This study aimed to develo...
PURPOSE: High quality scan prescription that optimally covers the area of interest with scan planes aligned to relevant anatomical structures is crucial for error-free radiologic interpretation. The goal of this project was to develop a machine learn...
BACKGROUND: ChatGPT is an open-source natural language processing software that replies to users' queries. We conducted a cross-sectional study to assess people living with Multiple Sclerosis' (PwMS) preferences, satisfaction, and empathy toward two ...
PURPOSE: To evaluate a deep learning reconstruction for turbo spin echo (DLR-TSE) sequence of ankle magnetic resonance imaging (MRI) in terms of acquisition time, image quality, and lesion detectability by comparing with conventional TSE.
Deep learning techniques have become crucial in the detection of brain tumors but classifying numerous images is time-consuming and error-prone, impacting timely diagnosis. This can hinder the effectiveness of these techniques in detecting brain tumo...
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Apr 3, 2024
BACKGROUND: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in medical care and research, including the efficient labeling and classification of unstructured text su...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.