AIMC Topic: Radiomics
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Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images.
BMC musculoskeletal disorders
May 20, 2025
OBJECTIVE: The aim of this study was to develop a hybrid diagnostic framework integrating radiomic and deep features for accurate and reproducible detection and classification of wrist fractures using X-ray images.
Prediction of prognosis of immune checkpoint inhibitors combined with anti-angiogenic agents for unresectable hepatocellular carcinoma by machine learning-based radiomics.
BMC cancer
May 19, 2025
OBJECTIVES: This study aims to develop and validate a novel radiomics model utilizing magnetic resonance imaging (MRI) to predict progression-free survival (PFS) in patients with unresectable hepatocellular carcinoma (uHCC) who are receiving a combin...
Humans
Aged
Adult
Radiomics
Male
Middle Aged
Machine Learning
Prognosis
Retrospective Studies
Female
Angiogenesis Inhibitors
Liver Neoplasms
Antineoplastic Combined Chemotherapy Protocols
Carcinoma, Hepatocellular
Magnetic Resonance Imaging
Immune Checkpoint Inhibitors
Progression-Free Survival
Nomograms
Assessing fetal lung maturity: Integration of ultrasound radiomics and deep learning.
African journal of reproductive health
May 16, 2025
This study built a model to forecast the maturity of lungs by blending radiomics and deep learning methods. We examined ultrasound images from 263 pregnancies in the pregnancy stages. Utilizing the GE VOLUSON E8 system we captured images to extract a...
Multicenter development of a deep learning radiomics and dosiomics nomogram to predict radiation pneumonia risk in non-small cell lung cancer.
Scientific reports
May 16, 2025
Radiation pneumonia (RP) is the most common side effect of chest radiotherapy, and can affect patients' quality of life. This study aimed to establish a combined model of radiomics, dosiomics, deep learning (DL) based on simulated location CT and dos...
Does Whole Brain Radiomics on Multimodal Neuroimaging Make Sense in Neuro-Oncology? A Proof of Concept Study.
Studies in health technology and informatics
May 15, 2025
Employing a whole-brain (WB) mask as a region of interest for extracting radiomic features is a feasible, albeit less common, approach in neuro-oncology research. This study aims to evaluate the relationship between WB radiomic features, derived from...
Deep learning MRI-based radiomic models for predicting recurrence in locally advanced nasopharyngeal carcinoma after neoadjuvant chemoradiotherapy: a multi-center study.
Clinical & experimental metastasis
May 15, 2025
Local recurrence and distant metastasis were a common manifestation of locoregionally advanced nasopharyngeal carcinoma (LA-NPC) after neoadjuvant chemoradiotherapy (NACT). To validate the clinical value of MRI radiomic models based on deep learning ...
A fully automatic radiomics pipeline for postoperative facial nerve function prediction of vestibular schwannoma.
Neuroscience
May 14, 2025
Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the options for the treatment of VS, with the preservation of facial nerve (FN) function being the primary objective. Therefore, postoperative FN function pre...
An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.
Scientific reports
May 13, 2025
The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer learning (DTL) features to predict meningioma grade. Three hundred forty meningiomas from one hospital composed the training set, and 102 meningiomas fr...
Identification of HER2-over-expression, HER2-low-expression, and HER2-zero-expression statuses in breast cancer based on F-FDG PET/CT radiomics.
Cancer imaging : the official publication of the International Cancer Imaging Society
May 12, 2025
PURPOSE: According to the updated classification system, human epidermal growth factor receptor 2 (HER2) expression statuses are divided into the following three groups: HER2-over-expression, HER2-low-expression, and HER2-zero-expression. HER2-negati...
A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights.
BMC gastroenterology
May 10, 2025
OBJECTIVE: This study aims to create a reliable framework for grading esophageal cancer. The framework combines feature extraction, deep learning with attention mechanisms, and radiomics to ensure accuracy, interpretability, and practical use in tumo...
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