Kun Q. Tang

Xuefu North Road
Wenzhou, 325000, China

Last Updated: 09/26/2026

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Found 62 publications

A Dual-phase Enhanced CT-based Nomogram for Predicting the Response to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

A Dual-phase Enhanced CT-based Nomogram for Predicting the Response to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

Journal: Academic radiology

Published: September 25, 2025

Computed tomography-based tumoral and peritumoral radiomics models for preoperative prediction of the spread through air spaces in patients with clinical stage I pure solid invasive lung adenocarcinoma: a multicenter study.

Computed tomography-based tumoral and peritumoral radiomics models for preoperative prediction of the spread through air spaces in patients with clinical stage I pure solid invasive lung adenocarcinoma: a multicenter study.

Journal: Journal of thoracic disease

Published: August 19, 2025

An explainable CT-based machine learning model integrating carotid plaque and perivascular adipose tissue for predicting symptomatic plaques.

An explainable CT-based machine learning model integrating carotid plaque and perivascular adipose tissue for predicting symptomatic plaques.

Journal: Frontiers in neurology

Published: August 05, 2025

CT-based delta-radiomics nomogram to assess tumor regression grade in locally advanced gastric cancer patients following neoadjuvant chemotherapy.

CT-based delta-radiomics nomogram to assess tumor regression grade in locally advanced gastric cancer patients following neoadjuvant chemotherapy.

Journal: Abdominal radiology (New York)

Published: July 08, 2025

The value of 18 F-2-fluoro-2-deoxyglucose PET/computed tomography radiomics in epidermal growth factor receptor mutation subtypes prediction and progression-free survival in advanced lung adenocarcinoma patients with first-line epidermal growth factor receptor tyrosine kinase inhibitors therapy.

The value of 18 F-2-fluoro-2-deoxyglucose PET/computed tomography radiomics in epidermal growth factor receptor mutation subtypes prediction and progression-free survival in advanced lung adenocarcinoma patients with first-line epidermal growth factor receptor tyrosine kinase inhibitors therapy.

Journal: Nuclear medicine communications

Published: April 26, 2025

Corrigendum: The value of targeted CXCR4 18F-AlF-NOTA-pentixafor PET/CT for subtyping primary aldosteronism.

Corrigendum: The value of targeted CXCR4 18F-AlF-NOTA-pentixafor PET/CT for subtyping primary aldosteronism.

Journal: Frontiers in endocrinology

Published: March 14, 2025

Construction of a prognostic model and identification of key genes in liver hepatocellular carcinoma based on multi-omics data.

Construction of a prognostic model and identification of key genes in liver hepatocellular carcinoma based on multi-omics data.

Journal: Scientific reports

Published: December 10, 2024

Development of a PET-CT Based Radiomics Model for Preoperative Prediction of the Novel IASLC Grading and Prognosis in Patients with Clinical Stage I Pure Solid Invasive Lung Adenocarcinoma.

Development of a PET-CT Based Radiomics Model for Preoperative Prediction of the Novel IASLC Grading and Prognosis in Patients with Clinical Stage I Pure Solid Invasive Lung Adenocarcinoma.

Journal: Academic radiology

Published: November 28, 2024

The effect of oral nutritional supplementation combined with probiotics on the liver function and intestinal microflora in lung cancer chemotherapy patients through the gut-liver axis.

The effect of oral nutritional supplementation combined with probiotics on the liver function and intestinal microflora in lung cancer chemotherapy patients through the gut-liver axis.

Journal: Scientific reports

Published: November 25, 2024

The value of targeted CXCR4 18F-AlF-NOTA-pentixafor PET/CT for subtyping primary aldosteronism.

The value of targeted CXCR4 18F-AlF-NOTA-pentixafor PET/CT for subtyping primary aldosteronism.

Journal: Frontiers in endocrinology

Published: November 23, 2024

Explainable PET-Based Habitat and Peritumoral Machine Learning Model for Predicting Progression-free Survival in Clinical Stage IA Pure-Solid Non-small Cell Lung Cancer: A Two-center Study.

Explainable PET-Based Habitat and Peritumoral Machine Learning Model for Predicting Progression-free Survival in Clinical Stage IA Pure-Solid Non-small Cell Lung Cancer: A Two-center Study.

Journal: Academic radiology

Published: November 23, 2024

Explainable PET-based intratumoral and peritumoral machine learning model for predicting visceral pleural invasion in clinical-stage IA non-small cell lung cancer: A two-center study.

Explainable PET-based intratumoral and peritumoral machine learning model for predicting visceral pleural invasion in clinical-stage IA non-small cell lung cancer: A two-center study.

Journal: Clinical radiology

Published: August 29, 2024

Showing 1-12 of 62

Last Updated: 09/26/2026