AIMC Topic: Radiomics
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Development and validation a radiomics combined clinical model predicts treatment response for esophageal squamous cell carcinoma patients.
BMC gastroenterology
Apr 29, 2025
PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiomics and clinical characteristics to predicting the definitive chemoradiotherapy (dCRT) treatment response in esophageal squamous cell carcinoma (ESCC)...
From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.
Neurosurgical review
Apr 29, 2025
Gliomas are the most common primary tumors of the central nervous system, and advances in genetics and molecular medicine have significantly transformed their classification and treatment. This study aims to predict the IDH1 genotype in gliomas using...
Machine Learning-Based Radiomics in Malignancy Prediction of Pancreatic Cystic Lesions: Evidence from Cyst Fluid Multi-Omics.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Apr 28, 2025
The malignant potential of pancreatic cystic lesions (PCLs) varies dramatically, leading to difficulties when making clinical decisions. This study aimed to develop noninvasive clinical-radiomic models using preoperative CT images to predict the mali...
Radiomics-based analysis of choroid plexus abnormalities in neuromyelitis optica spectrum disorders and multiple sclerosis and their clinical implications.
Multiple sclerosis and related disorders
Apr 22, 2025
BACKGROUND: The choroid plexus (CP) is closely linked to inflammation in multiple sclerosis (MS). While the CP volume is enlarged in MS compared with healthy controls (HC), no such changes are observed in neuromyelitis optica spectrum disorder (NMOSD...
X-ray based radiomics machine learning models for predicting collapse of early-stage osteonecrosis of femoral head.
Scientific reports
Apr 20, 2025
This study aimed to develop an X-ray radiomics model for predicting collapse of early-stage osteonecrosis of the femoral head (ONFH). A total of 87 patients (111 hips; training set: n = 67, test set: n = 44) with non-traumatic ONFH at Association Res...
Federated Learning in radiomics: A comprehensive meta-survey on medical image analysis.
Computer methods and programs in biomedicine
Apr 19, 2025
Federated Learning (FL) has emerged as a promising approach for collaborative medical image analysis while preserving data privacy, making it particularly suitable for radiomics tasks. This paper presents a systematic meta-analysis of recent surveys ...
Prediction of early recurrence in primary central nervous system lymphoma based on multimodal MRI-based radiomics: A preliminary study.
European journal of radiology
Apr 18, 2025
OBJECTIVES: To evaluate the role of multimodal magnetic resonance imaging radiomics features in predicting early recurrence of primary central nervous system lymphoma (PCNSL) and to investigate their correlation with patient prognosis.
Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.
Scientific reports
Apr 18, 2025
This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differential anti-vascular endothelial growth factor (VEGF) treatment outcomes using an unsupervised machine learning (ML) approach based on radiomic feature...
Humans
Diabetic Retinopathy
Retrospective Studies
Female
Aged
Radiomics
Male
Middle Aged
Visual Acuity
Angiogenesis Inhibitors
Principal Component Analysis
Treatment Outcome
Tomography, Optical Coherence
Cluster Analysis
Macular Edema
Unsupervised Machine Learning
Vascular Endothelial Growth Factor A
Automated opportunistic screening for osteoporosis using deep learning-based automatic segmentation and radiomics on proximal femur images from low-dose abdominal CT.
BMC musculoskeletal disorders
Apr 17, 2025
RATIONALE AND OBJECTIVES: To establish an automated osteoporosis detection model based on low-dose abdominal CT (LDCT). This model combined a deep learning-based automatic segmentation of the proximal femur with a radiomics-based bone status classifi...
A radiomics approach to distinguish Progressive Supranuclear Palsy Richardson's syndrome from other phenotypes starting from MR images.
Computer methods and programs in biomedicine
Apr 13, 2025
BACKGROUND AND OBJECTIVE: Progressive Supranuclear Palsy (PSP) is an uncommon neurodegenerative disorder with different clinical onset, including Richardson's syndrome (PSP-RS) and other variant phenotypes (vPSP). Recognising the clinical progression...
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