predicting-traditional-chinese-medicine-rehabilitation-acute-ischemic

Predicting Traditional Chinese Medicine Rehabilitation in Acute Ischemic Stroke Using Multiphase CT Angiography Collateral Scores

The present study evaluated the predictive value of multiphase computed tomography (CT) angiography (mCTA) collateral circulation scores in determining ...

Department of Radiology Affiliated Hospital of Southwest Medical University Luzhou

Affiliated Hospital of Southwest Medical University

To develop and validate a model integrating dual-layer detector spectral computed tomography (DLCT) three-dimensional (3D) volume of interest (VOI)-based quantitative parameters and clinical features for predicting Ki-67 proliferation index (PI) in pancreatic ductal adenocarcinoma (PDAC).

Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-based quantitative parameters to predict high Ki-67 proliferation index in pancreatic ductal adenocarcinoma.

To evaluate the feasibility of radiomics analysis using dual-layer detector spectral CT (DLCT)-derived iodine maps for the preoperative prediction of the Ki-67 proliferation index (PI) in pancreatic ductal adenocarcinoma (PDAC).

Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal adenocarcinoma.

More cases of thyroid micro-nodules have been diagnosed annually in recent years because of advancements in diagnostic technologies and increased public health awareness. To explore the application value of various machine learning (ML) algorithms based on dual-layer spectral computed tomography (DLCT) quantitative parameters in distinguishing benign from malignant thyroid micro-nodules.

The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules.

Machine learning model incorporating spectral CT quantitative parameters and clinical characteristics for differentiation of benign and malignant thyroid nodules.

Article	Year
Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-based quantitative parameters to predict high Ki-67 proliferation index in... Insights into imaging\| PubMed ID: 39636501	2024
Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal adenocarcinoma. BMC medical imaging\| PubMed ID: 40247246	2025
The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules. BMC cancer\| PubMed ID: 40597056	2025
Machine learning model incorporating spectral CT quantitative parameters and clinical characteristics for differentiation of benign and malignant thyroid nodules. BMC medical imaging\| PubMed ID: 41286692	2025

Zhuoyue Tang

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