AIMC Topic: Radiomics
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Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Nov 18, 2024
OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) and construct a tool for preoperative noninvasive predicting FTC and FTA.
A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.
Acta radiologica (Stockholm, Sweden : 1987)
Nov 18, 2024
BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathological type of brain metastases (BMs).
Artificial intelligence-based personalized survival prediction using clinical and radiomics features in patients with advanced non-small cell lung cancer.
BMC cancer
Nov 18, 2024
BACKGROUND: Multiple first-line treatment options have been developed for advanced non-small cell lung cancer (NSCLC) in each subgroup determined by predictive biomarkers, specifically driver oncogene and programmed cell death ligand-1 (PD-L1) status...
Prediction of esophageal fistula in radiotherapy/chemoradiotherapy for patients with advanced esophageal cancer by a clinical-deep learning radiomics model : Prediction of esophageal fistula in radiotherapy/chemoradiotherapy patients.
BMC medical imaging
Nov 18, 2024
BACKGROUND: Esophageal fistula (EF), a rare and potentially fatal complication, can be better managed with predictive models for personalized treatment plans in esophageal cancers. We aim to develop a clinical-deep learning radiomics model for effect...
An arterial spin labeling-based radiomics signature and machine learning for the prediction and detection of various stages of kidney damage due to diabetes.
Frontiers in endocrinology
Nov 18, 2024
OBJECTIVE: The aim of this study was to assess the predictive capabilities of a radiomics signature obtained from arterial spin labeling (ASL) imaging in forecasting and detecting stages of kidney damage in patients with diabetes mellitus (DM), as we...
Preoperative prediction of post hepatectomy liver failure after surgery for hepatocellular carcinoma on CT-scan by machine learning and radiomics analyses.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Nov 15, 2024
INTRODUCTION: No instruments are available to predict preoperatively the risk of posthepatectomy liver failure (PHLF) in HCC patients. The aim was to predict the occurrence of PHLF preoperatively by radiomics and clinical data through machine-learnin...
Improved prognostication of overall survival after radiotherapy in lung cancer patients by an interpretable machine learning model integrating lung and tumor radiomics and clinical parameters.
La Radiologia medica
Nov 14, 2024
BACKGROUND: Accurate prognostication of overall survival (OS) for non-small cell lung cancer (NSCLC) patients receiving definitive radiotherapy (RT) is crucial for developing personalized treatment strategies. This study aims to construct an interpre...
Predicting craniofacial fibrous dysplasia growth status: an exploratory study of a hybrid radiomics and deep learning model based on computed tomography images.
Oral surgery, oral medicine, oral pathology and oral radiology
Nov 12, 2024
OBJECTIVE: This study aimed to develop 3 models based on computed tomography (CT) images of patients with craniofacial fibrous dysplasia (CFD): a radiomics model (Model Rad), a deep learning (DL) model (Model DL), and a hybrid radiomics and DL model ...
A F-FDG PET/CT-based deep learning-radiomics-clinical model for prediction of cervical lymph node metastasis in esophageal squamous cell carcinoma.
Cancer imaging : the official publication of the International Cancer Imaging Society
Nov 12, 2024
BACKGROUND: To develop an artificial intelligence (AI)-based model using Radiomics, deep learning (DL) features extracted from F-fluorodeoxyglucose (F-FDG) Positron emission tomography/Computed Tomography (PET/CT) images of tumor and cervical lymph n...
Diagnostic and predictive value of radiomics-based machine learning for intracranial aneurysm rupture status: a systematic review and meta-analysis.
Neurosurgical review
Nov 12, 2024
Currently, the growing interest in radiomics within the clinical practice has prompted some researchers to differentiate the rupture status of intracranial aneurysm (IA) by developing radiomics-based machine learning models. However, systematic evide...
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