OBJECTIVES: This study aims to develop a deep learning algorithm (DLA) using the InceptionV3 architecture for effective diabetic peripheral neuropathy (DPN) screening via corneal confocal microscopy (CCM) images.
BACKGROUND: Artificial intelligence-powered chatbots (AI-PCs) are increasingly integrated into educational settings, including health care disciplines. Despite their potential to enhance learning, limited research has investigated physiotherapy (PT) ...
BACKGROUND: This study aims to apply a semi-supervised machine learning approach for classifying major depressive disorder (MDD) patients into more homogeneous cognitive subtypes based on multidimensional cognitive profiles, and to perform multimodal...
The American journal of sports medicine
Aug 15, 2025
BACKGROUND: Treatment decisions in patients with anterior cruciate ligament (ACL) injuries are influenced by multiple factors, such as the desire to return to sports or symptomatic instability. Identifying the differential treatment effect of ACL rec...
The study's central objective is to harness the power of generative Artificial Intelligence (AI), in particular based on Large Language Models, as a valuable resource for delving deeper into the insights offered by patients with breast cancer (BC) wh...
BACKGROUND: Recently, robotic arms have been incorporated into the implantation of electrodes for deep brain stimulation (DBS).This study aimed to determine the accuracy of brain electrode placement, initial clinical efficacy, and safety profile of t...
BACKGROUND: We aimed to quantify hepatic vessel volumes across chronic liver disease stages and healthy controls using deep learning-based magnetic resonance imaging (MRI) analysis, and assess correlations with biomarkers for liver (dys)function and ...
Interstitial lung disease (ILD) is a common and serious organ manifestation in patients with connective tissue disease (CTD), but it is uncertain whether there is a difference in ILD between symptomatic and asymptomatic patients. Therefore, we conduc...
OBJECTIVES: The aim of this study was to evaluate GPT-4o's multimodal reasoning ability to review panoramic radiograph (PR) and verify its radiologic findings, while exploring the role of prompt engineering in enhancing its performance.
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