AIMC Topic: Radiomics

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Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism.

Academic radiology Dec 1, 2023
RATIONALE AND OBJECTIVES: Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography ...
Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Humans Middle Aged Hyperaldosteronism Aldosterone Adrenal Glands Aged Adult Radiomics Male
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Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors.

Journal of magnetic resonance imaging : JMRI Nov 29, 2023
BACKGROUND: Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored.
Radiomics Central Nervous System Neoplasms Magnetic Resonance Imaging Female Middle Aged Brain Neoplasms Reproducibility of Results Male Humans Neoplasm Grading World Health Organization ROC Curve Aged Image Processing, Computer-Assisted Adult Glioma Machine Learning Retrospective Studies
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Constructing a Deep Learning Radiomics Model Based on X-ray Images and Clinical Data for Predicting and Distinguishing Acute and Chronic Osteoporotic Vertebral Fractures: A Multicenter Study.

Academic radiology Nov 27, 2023
RATIONALE AND OBJECTIVES: To construct and validate a deep learning radiomics (DLR) model based on X-ray images for predicting and distinguishing acute and chronic osteoporotic vertebral fractures (OVFs).
Acute Disease Spinal Fractures Humans Osteoporotic Fractures Prospective Studies Magnetic Resonance Imaging Female Male Aged Diagnosis, Differential Middle Aged Aged, 80 and over Chronic Disease Deep Learning Radiomics Nomograms
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Prediction of recurrence risk factors in patients with early-stage cervical cancers by nomogram based on MRI handcrafted radiomics features and deep learning features: a dual-center study.

Abdominal radiology (New York) Nov 21, 2023
PURPOSE: To establish and validate a deep learning radiomics nomogram (DLRN) based on intratumoral and peritumoral regions of MR images and clinical characteristics to predict recurrence risk factors in early-stage cervical cancer and to clarify whet...
Retrospective Studies Female Risk Factors Radiomics Uterine Cervical Neoplasms Deep Learning Nomograms Humans Magnetic Resonance Imaging
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AdaRes: A deep learning-based model for ultrasound image denoising: Results of image quality metrics, radiomics, artificial intelligence, and clinical studies.

Journal of clinical ultrasound : JCU Nov 20, 2023
PURPOSE: The quality of ultrasound images is degraded by speckle and Gaussian noises. This study aims to develop a deep-learning (DL)-based filter for ultrasound image denoising.
Radiomics Humans Artificial Intelligence Deep Learning Ultrasonography Signal-To-Noise Ratio
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Development and Validation of a Machine Learning-Based Model Using CT Radiomics for Predicting Immune Checkpoint Inhibitor-related Pneumonitis in Patients With NSCLC Receiving Anti-PD1 Immunotherapy: A Multicenter Retrospective CaseControl Study.

Academic radiology Nov 17, 2023
RATIONALE AND OBJECTIVES: This study aimed to develop and evaluate a radiomics-based model combined with clinical and qualitative radiological (semantic feature [SF]) features to predict immune checkpoint inhibitor-related pneumonitis (CIP) in patien...
Immunotherapy Carcinoma, Non-Small-Cell Lung Pneumonia Middle Aged Humans Immune Checkpoint Inhibitors Machine Learning Female Lung Neoplasms Retrospective Studies Aged Tomography, X-Ray Computed Radiomics Male
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Editorial for "Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures".

Journal of magnetic resonance imaging : JMRI Nov 16, 2023
Brain Radiomics Brain Neoplasms Deep Learning Magnetic Resonance Imaging Diagnosis, Differential Glioblastoma Humans
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Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT.

La Radiologia medica Nov 16, 2023
OBJECTIVES: The study aimed to develop a combined model that integrates deep learning (DL), radiomics, and clinical data to classify lung nodules into benign or malignant categories, and to further classify lung nodules into different pathological su...
Lung Deep Learning Lung Neoplasms Humans Tomography, X-Ray Computed Radiomics
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Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.

Journal of magnetic resonance imaging : JMRI Nov 13, 2023
BACKGROUND: Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic-MRI and DLR features can more accurately distinguish GBM from SBM ...
Humans Adult Radiomics Brain Neoplasms Male Brain Retrospective Studies Female Aged Magnetic Resonance Imaging Middle Aged Diagnosis, Differential Deep Learning Glioblastoma Nomograms
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Editorial for "A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI".

Journal of magnetic resonance imaging : JMRI Nov 10, 2023
Image Interpretation, Computer-Assisted Diffusion Magnetic Resonance Imaging Machine Learning Female Breast Neoplasms Radiomics Magnetic Resonance Imaging Humans Diagnosis, Differential Breast
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