Muscle ultrasound has high utility in clinical practice and research; however, the main challenges are the training and time required for manual analysis to achieve objective quantification of muscle size and quality. We aimed to develop and validate...
BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasively predicting high-grade patterns (HGPs) of invasive lung adenocarcinoma (LUAD).
European journal of nuclear medicine and molecular imaging
Apr 25, 2025
PURPOSE: To assess feasibility of lung cancer screening, we analysed lung lesion detectability simulating low-dose and convolutional neural network (CNN) denoised [F]-FDG PET/CT reconstructions.
INTRODUCTION: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and time factors. Machine learning offers powerful tools...
Journal of applied clinical medical physics
Apr 23, 2025
BACKGROUND: Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning-based automatic segmentation methods rely on manually annotated data for network training.
Patients with lung metastasis of colorectal cancer typically have a poor prognosis. Therefore, establishing an effective screening and diagnosis model is paramount. Our study seeks to construct and verify a predictive model utilizing machine learning...
BACKGROUND: Lymphovascular invasion (LVI) is a significant histopathological marker associated with poor prognosis in patients. However, there is a notable lack of reliable, non-invasive preoperative tools to predict LVI accurately.
RATIONALE AND OBJECTIVES: The research aims to examine how CT-derived habitat radiomics can be used to predict lymphovascular invasion (LVI) in patients with T1-stage lung adenocarcinoma (LUAD), and compare its effectiveness to traditional radiomics ...
BACKGROUND: Visceral pleural invasion (VPI), including PL1 (the tumor invades beyond the elastic layer) and PL2 (the tumor extends to the surface of the visceral pleura), plays a crucial role in staging Non-Small Cell Lung Cancer (NSCLC). However, th...
BMC medical informatics and decision making
Apr 18, 2025
The automated processing of Electronic Health Records (EHRs) poses a significant challenge due to their unstructured nature, rich in valuable, yet disorganized information. Natural Language Processing (NLP), particularly Named Entity Recognition (NER...
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