Radiomics has become a research field that involves the process of converting standard
nursing images into quantitative image data, which can be combined with other data …

Objectives This study evaluates the accuracy of radiomics in predicting lymph node
metastasis in non-small cell lung cancer, which is crucial for patient management and …

Ultrasound-based models exist to support the classification of adnexal masses but are
subjective and rely upon ultrasound expertise. We aimed to develop an end-to-end machine …

Background Radiomics, which involves the conversion of digital images into high-
dimensional data, has been used in oncological studies since 2012. We analyzed the …

Background Whether lymph node metastasis in non-small cell lung cancer is critical to
clinical decision-making. This study was to develop a non-invasive predictive model for …

Early and precise detection of lung tumor cell is paramount for providing adequate
medication and increasing the survivability of the patients. To achieve this, the Enhanced …

CT scans efficiently detect lung cancer. A good prediction method is crucial. Recently, deep
convolutional neural networks (CNN) have influenced picture categorization algorithms. This …

Purpose: Create a deep learning-based radiomics framework to anticipate prediction
models for advanced lung adenocarcinoma with brain metastases. This aims to inform …