Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analysis of this disorder contains various tests, namely ultrasound (US), magnetic resonance imaging (MRI), and computed tomography (CT). Despite analytica...
PURPOSE: The clinical implications of coronary artery calcification (CAC) growth remain underexplored. This study aims to assess CAC growth and its association with adverse cardiovascular events (ACEs) in individuals undergoing lung cancer screening ...
Acute Respiratory Distress Syndrome (ARDS) is a life-threatening condition characterized by acute onset of respiratory failure, which presents significant challenges in diagnosis and management. Its heterogeneity, with diverse underlying aetiologies ...
BACKGROUND: Crohn's disease (CD) is a chronic inflammatory bowel disease, with infliximab (IFX) commonly used for treatment. However, no clinically applicable model currently exists to predict the response of patients with CD to IFX therapy. Given th...
RATIONALE AND OBJECTIVES: Large Language Models (LLMs) show promise for generating patient-friendly radiology reports, but the performance of open-source versus proprietary LLMs needs assessment. To compare open-source and proprietary LLMs in generat...
INTRODUCTION: In China, there is a lack of standardised clinical imaging databases for multidimensional evaluation of cardiopulmonary diseases. To address this gap, this study protocol launched a project to build a clinical imaging technology integra...
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model that integrates radiomics and conventional radiological features to predict the success of single-session extracorporeal shock wave lithotripsy (ESWL) for ureteral sto...
Deep learning has been used for automatic planning of radiotherapy targets, such as inferring the clinical target volume (CTV) for a given new patient. However, previous deep learning methods mainly focus on predicting CTV from CT images without cons...
Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are essential clinical cross-sectional imaging techniques for diagnosing complex conditions. However, large 3D datasets with annotations for deep learning are scarce. While methods like DI...
Early lung cancer invasive detection is important for further treatment and saving lives. In clinical practice, lung tumor invasiveness (LTI) detection is very challenging, imaging-based automatic prediction algorithms offer a non-invasive approach. ...
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