AIMC Topic: Radiomics
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Radiomics for lung cancer diagnosis, management, and future prospects.
Clinical radiology
Apr 11, 2025
Lung cancer remains the leading cause of cancer-related mortality worldwide, with its early detection and effective treatment posing significant clinical challenges. Radiomics, the extraction of quantitative features from medical imaging, has emerged...
Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single-center retrospective study in China.
Journal of applied clinical medical physics
Apr 11, 2025
PURPOSE: To assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC).
Predicting PD-L1 status in NSCLC patients using deep learning radiomics based on CT images.
Scientific reports
Apr 11, 2025
Radiomics refers to the utilization of automated or semi-automated techniques to extract and analyze numerous quantitative features from medical images, such as computerized tomography (CT) or magnetic resonance imaging (MRI) scans. This study aims t...
Machine-Learning-Based Computed Tomography Radiomics Regression Model for Predicting Pulmonary Function.
Academic radiology
Apr 10, 2025
RATIONALE AND OBJECTIVES: Chest computed tomography (CT) radiomics can be utilized for categorical predictions; however, models predicting pulmonary function indices directly are lacking. This study aimed to develop machine-learning-based regression ...
Interpretable Machine Learning Radiomics Model Predicts 5-year Recurrence-Free Survival in Non-metastatic Clear Cell Renal Cell Carcinoma: A Multicenter and Retrospective Cohort Study.
Academic radiology
Apr 10, 2025
RATIONALE AND OBJECTIVES: To develop and validate a computed tomography (CT) radiomics-based interpretable machine learning (ML) model for predicting 5-year recurrence-free survival (RFS) in non-metastatic clear cell renal cell carcinoma (ccRCC).
Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks.
BMC cancer
Apr 10, 2025
OBJECTIVE: The infiltration status of pulmonary ground-glass nodules (GGNs) exhibits significant variability, demanding tailored surgical strategies and individualized postoperative adjuvant therapies. This study explored the preoperative assessment ...
Habitat Radiomics Based on MRI for Predicting Metachronous Liver Metastasis in Locally Advanced Rectal Cancer: a Two‑center Study.
Academic radiology
Apr 9, 2025
RATIONALE AND OBJECTIVES: This study aimed to explore the feasibility of using habitat radiomics based on magnetic resonance imaging (MRI) to predict metachronous liver metastasis (MLM) in locally advanced rectal cancer (LARC) patients. A nomogram wa...
Novel deep learning algorithm based MRI radiomics for predicting lymph node metastases in rectal cancer.
Scientific reports
Apr 9, 2025
To explore the value of applying the MRI-based radiomic nomogram for predicting lymph node metastasis (LNM) in rectal cancer (RC). This retrospective analysis used data from 430 patients with RC from two medical centers. The patients were categorized...
Prediction of Seronegative Hashimoto's thyroiditis using machine learning models based on ultrasound radiomics: a multicenter study.
BMC immunology
Apr 7, 2025
BACKGROUND: Seronegative Hashimoto's thyroiditis is often underdiagnosed due to the lack of antibody markers. Combining ultrasound radiomics with machine learning offers potential for early detection in patients with normal thyroid function.
Radiomics across modalities: a comprehensive review of neurodegenerative diseases.
Clinical radiology
Apr 3, 2025
Radiomics allows extraction from medical images of quantitative features that are able to reveal tissue patterns that are generally invisible to human observers. Despite the challenges in visually interpreting radiomic features and the computational ...
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