Radiomics

Lung nodule classification using radiomics model trained on degraded SDCT images.

Computer methods and programs in biomedicine Oct 23, 2024

BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) screening has shown promise in reducing lung cancer mortality; however, it suffers from high false positive rates and a scarcity of available annotated datasets. To overcome these challeng...

Logistic Models Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans Reproducibility of Results Radiomics Image Processing, Computer-Assisted Lung Neoplasms Machine Learning Algorithms Tomography, X-Ray Computed

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Multimodal radiomics and deep learning models for predicting early femoral head deformity in LCPD.

European journal of radiology Oct 19, 2024

PURPOSE: To develop a predictive model combining clinical, radiomic, and deep learning features based on X-ray and MRI to identify risk factors for early femoral head deformity in Legg-Calvé-Perthes disease (LCPD).

Humans Retrospective Studies Female Radiomics Child, Preschool Child Magnetic Resonance Imaging Male Deep Learning Multimodal Imaging Predictive Value of Tests Femur Head Legg-Calve-Perthes Disease

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Machine learning-based CT radiomics approach for predicting occult peritoneal metastasis in advanced gastric cancer preoperatively.

Clinical radiology Oct 18, 2024

AIM: To develop a machine learning-based CT radiomics model to preoperatively diagnose occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients.

Stomach Neoplasms Radiomics Female Male Humans Peritoneal Neoplasms Nomograms Aged Middle Aged Machine Learning Aged, 80 and over Predictive Value of Tests Retrospective Studies Adult Tomography, X-Ray Computed

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Deep learning radiomic nomogram outperforms the clinical model in distinguishing intracranial solitary fibrous tumors from angiomatous meningiomas and can predict patient prognosis.

European radiology Oct 16, 2024

OBJECTIVES: To evaluate the value of a magnetic resonance imaging (MRI)-based deep learning radiomic nomogram (DLRN) for distinguishing intracranial solitary fibrous tumors (ISFTs) from angiomatous meningioma (AMs) and predicting overall survival (OS...

Female Aged Adult Radiomics Brain Neoplasms Humans Prognosis Retrospective Studies Magnetic Resonance Imaging Male Diagnosis, Differential Middle Aged Meningioma Deep Learning Meningeal Neoplasms Nomograms Solitary Fibrous Tumors

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Multiparametric MRI Radiomics With Machine Learning for Differentiating HER2-Zero, -Low, and -Positive Breast Cancer: Model Development, Testing, and Interpretability Analysis.

AJR. American journal of roentgenology Oct 16, 2024

MRI radiomics has been explored for three-tiered classification of HER2 expression levels (i.e., HER2-zero, HER2-low, or HER2-positive) in patients with breast cancer, although an understanding of how such models reach their predictions is lacking. ...

Female Aged Adult Breast Neoplasms Radiomics Humans Machine Learning Retrospective Studies Receptor, ErbB-2 Multiparametric Magnetic Resonance Imaging Middle Aged Magnetic Resonance Imaging Breast Image Interpretation, Computer-Assisted

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Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features.

International journal of computer assisted radiology and surgery Oct 7, 2024

PURPOSE: This study investigates the application of Radiomic features within graph neural networks (GNNs) for the classification of multiple-epitope-ligand cartography (MELC) pathology samples. It aims to enhance the diagnosis of often misdiagnosed s...

Graph Neural Networks Radiomics Skin Diseases Image Interpretation, Computer-Assisted Humans Neural Networks, Computer

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Machine learning based classification of spontaneous intracranial hemorrhages using radiomics features.

Neuroradiology Oct 5, 2024

PURPOSE: To assess the efficacy of radiomics features extracted from non-contrast computed tomography (NCCT) scans in differentiating multiple etiologies of spontaneous intracerebral hemorrhage (ICH).

Humans Machine Learning Retrospective Studies Middle Aged Adult Diagnosis, Differential Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Radiomics Intracranial Hemorrhages Female Male Aged Aged, 80 and over

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Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy.

Annals of surgical oncology Oct 5, 2024

OBJECTIVES: This study was designed to assess computed tomography (CT)-based radiomics of colorectal liver metastases (CRLM), extracted from posttreatment scans in estimating pathologic treatment response to neoadjuvant therapy, and to compare treatm...

Female Aged Neoadjuvant Therapy Adult Follow-Up Studies Colorectal Neoplasms Radiologists Humans Middle Aged Radiomics Response Evaluation Criteria in Solid Tumors Machine Learning Liver Neoplasms Male Prognosis Antineoplastic Combined Chemotherapy Protocols Retrospective Studies Tomography, X-Ray Computed

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Machine learning and radiomics for ventricular tachyarrhythmia prediction in hypertrophic cardiomyopathy: insights from an MRI-based analysis.

Acta radiologica (Stockholm, Sweden : 1987) Oct 1, 2024

BACKGROUND: Myocardial fibrosis is often detected in patients with hypertrophic cardiomyopathy (HCM), which causes left ventricular (LV) dysfunction and tachyarrhythmias.

Magnetic Resonance Imaging, Cine Adult Radiomics Male Middle Aged Humans Machine Learning Predictive Value of Tests Retrospective Studies Contrast Media Cardiomyopathy, Hypertrophic Female Magnetic Resonance Imaging Tachycardia, Ventricular

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Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.

Acta radiologica (Stockholm, Sweden : 1987) Oct 1, 2024

BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign...

Aged, 80 and over Adult Radiomics Humans Male Machine Learning Fractures, Compression Retrospective Studies Middle Aged Tomography, X-Ray Computed Diagnosis, Differential Female Spinal Neoplasms Aged Spinal Fractures

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Explore the latest research on artificial intelligence and machine learning in medicine.

Lung nodule classification using radiomics model trained on degraded SDCT images.

Multimodal radiomics and deep learning models for predicting early femoral head deformity in LCPD.

Machine learning-based CT radiomics approach for predicting occult peritoneal metastasis in advanced gastric cancer preoperatively.

Deep learning radiomic nomogram outperforms the clinical model in distinguishing intracranial solitary fibrous tumors from angiomatous meningiomas and can predict patient prognosis.

Multiparametric MRI Radiomics With Machine Learning for Differentiating HER2-Zero, -Low, and -Positive Breast Cancer: Model Development, Testing, and Interpretability Analysis.

Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features.

Machine learning based classification of spontaneous intracranial hemorrhages using radiomics features.

Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy.

Machine learning and radiomics for ventricular tachyarrhythmia prediction in hypertrophic cardiomyopathy: insights from an MRI-based analysis.

Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.

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