AIMC Topic: Radiomics
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A pretreatment multiparametric MRI-based radiomics-clinical machine learning model for predicting radiation-induced temporal lobe injury in patients with nasopharyngeal carcinoma.
Head & neck
Jun 18, 2024
BACKGROUND: To establish and validate a machine learning model using pretreatment multiparametric magnetic resonance imaging-based radiomics data with clinical data to predict radiation-induced temporal lobe injury (RTLI) in patients with nasopharyng...
Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging.
Circulation. Cardiovascular imaging
Jun 18, 2024
Cardiovascular diseases remain a significant health burden, with imaging modalities like echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging playing a crucial role in diagnosis and prognosis. However, the inherent he...
A machine learning model based on clinical features and ultrasound radiomics features for pancreatic tumor classification.
Frontiers in endocrinology
Jun 17, 2024
OBJECTIVE: This study aimed to construct a machine learning model using clinical variables and ultrasound radiomics features for the prediction of the benign or malignant nature of pancreatic tumors.
Endoscopic ultrasonography-based intratumoral and peritumoral machine learning radiomics analyses for distinguishing insulinomas from non-functional pancreatic neuroendocrine tumors.
Frontiers in endocrinology
Jun 17, 2024
OBJECTIVES: To develop and validate radiomics models utilizing endoscopic ultrasonography (EUS) images to distinguish insulinomas from non-functional pancreatic neuroendocrine tumors (NF-PNETs).
Diagnostic accuracy of CT-based radiomics and deep learning for predicting lymph node metastasis in esophageal cancer.
Clinical imaging
Jun 16, 2024
BACKGROUND: Esophageal cancer remains a global challenge due to late diagnoses and limited treatments. Lymph node metastasis (LNM) is crucial for prognosis, yet traditional diagnostics fall short. Integrating radiomics and deep learning (DL) with CT ...
CT-based radiomics of machine-learning to screen high-risk individuals with kidney stones.
Urolithiasis
Jun 15, 2024
Screening high-risk populations is crucial for the prevention and treatment of kidney stones. Here, we employed radiomics to screen high-risk patients for kidney stones. A total of 513 independent kidneys from our hospital between 2020 and 2022 were ...
A machine learning radiomics based on enhanced computed tomography to predict neoadjuvant immunotherapy for resectable esophageal squamous cell carcinoma.
Frontiers in immunology
Jun 14, 2024
BACKGROUND: Patients with resectable esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant immunotherapy (NIT) display variable treatment responses. The purpose of this study is to establish and validate a radiomics based on enhanced comput...
Histological Subtype Classification of Non-Small Cell Lung Cancer with Radiomics and 3D Convolutional Neural Networks.
Journal of imaging informatics in medicine
Jun 11, 2024
Non-small cell lung carcinoma (NSCLC) is the most common type of pulmonary cancer, one of the deadliest malignant tumors worldwide. Given the increased emphasis on the precise management of lung cancer, identifying various subtypes of NSCLC has becom...
Predicting disease recurrence in breast cancer patients using machine learning models with clinical and radiomic characteristics: a retrospective study.
Journal of the Egyptian National Cancer Institute
Jun 10, 2024
BACKGROUND: The goal is to use three different machine learning models to predict the recurrence of breast cancer across a very heterogeneous sample of patients with varying disease kinds and stages.
Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method.
Breast cancer research and treatment
Jun 9, 2024
PURPOSE: This study aims to assess the diagnostic value of ultrasound habitat sub-region radiomics feature parameters using a fully connected neural networks (FCNN) combination method L2,1-norm in relation to breast cancer Ki-67 status.
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