AIMC Topic: Radiomics
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Integrating radiomics and gene expression by mapping on the image with improved DeepInsight for clear cell renal cell carcinoma.
Cancer genetics
Feb 14, 2025
BACKGROUND: Radiomics analysis extracts high-dimensional features from medical images, which are used to predict outcomes in machine learning (ML). Recently, deep-learning methods have become applicable to image data converted from nonimage samples.
An interpretable ensemble model combining handcrafted radiomics and deep learning for predicting the overall survival of hepatocellular carcinoma patients after stereotactic body radiation therapy.
Journal of cancer research and clinical oncology
Feb 14, 2025
PURPOSE: Hepatocellular carcinoma (HCC) remains a global health concern, marked by increasing incidence rates and poor outcomes. This study seeks to develop a robust predictive model by integrating radiomics and deep learning features with clinical d...
Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT.
PloS one
Feb 13, 2025
PURPOSE: This study aims to explore the potential of non-contrast abdominal CT radiomics and deep learning models in accurately diagnosing fatty liver.
Radiomics for differentiating radiation-induced brain injury from recurrence in gliomas: systematic review, meta-analysis, and methodological quality evaluation using METRICS and RQS.
European radiology
Feb 12, 2025
OBJECTIVE: To systematically evaluate glioma radiomics literature on differentiating between radiation-induced brain injury and tumor recurrence.
Comparative analysis of machine learning models for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer: An MRI radiomics approach.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Feb 12, 2025
PURPOSE: The aim of this work is to compare different machine learning models for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer using radiomics features from dynamic contrast-enhanced magnetic reso...
Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study.
Journal of cardiothoracic surgery
Feb 11, 2025
BACKGROUND: Radiomics has shown promise in the diagnosis and prognosis of lung cancer. Here, we investigated the performance of computed tomography-based radiomic features, extracted from gross tumor volume (GTV), peritumoral volume (PTV), and GTV + ...
Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.
Journal of medical systems
Feb 11, 2025
This study aims to apply a multi-modal approach of the deep learning method for survival prediction in patients with non-small-cell lung cancer (NSCLC) using CT-based radiomics. We utilized two public data sets from the Cancer Imaging Archive (TCIA) ...
Prediction of High-risk Capsule Characteristics for Recurrence of Pleomorphic Adenoma in the Parotid Gland Based on Habitat Imaging and Peritumoral Radiomics: A Two-center Study.
Academic radiology
Feb 10, 2025
RATIONALE AND OBJECTIVES: This study aims to develop and validate an ultrasoundbased habitat imaging and peritumoral radiomics model for predicting high-risk capsule characteristics for recurrence of pleomorphic adenoma (PA) of the parotid gland whil...
Ultrasonic-Based Radiomics Signature With Machine Learning for Differentiating Prognostic Subsets of Pediatric Peripheral Neuroblastic Tumors: A Retrospective Study.
Ultrasound in medicine & biology
Feb 8, 2025
OBJECTIVE: To construct and select a better model based on ultrasonic-based radiomics features and clinical characteristics for prognostic subsets of pediatric neuroblastic tumors.
A Hybrid Machine Learning CT-Based Radiomics Nomogram for Predicting Cancer-Specific Survival in Curatively Resected Colorectal Cancer.
Academic radiology
Feb 7, 2025
RATIONALE AND OBJECTIVES: To develop and validate a computed tomography-based radiomics nomogram for cancer-specific survival (CSS) prediction in curatively resected colorectal cancer (CRC), and its performance was compared with the American Joint Co...
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