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References from Interpretable machine learning integrating intra-/peritumoral CT radiomics and serum indicators for predicting poorly differentiated esophageal squamous cell carcinoma. Local targets link to admitted publications; unresolved targets remain external evidence.
Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
10.3322/caac.21660 · 2021 · External reference
International trends in esophageal cancer incidence rates by histological subtype (1990-2012) and prediction of the rates to 2030
10.1007/s10388-022-00927-4 · 2022 · External reference
Cancer statistics, 2024
10.3322/caac.21820 · 2024 · External reference
Spectral CT - a new supplementary method for preoperative assessment of pathological grades of esophageal squamous cell carcinoma
10.1186/s12880-023-01068-5 · 2023 · External reference
The clinical significance and potential molecular mechanism of PTTG1 in esophageal squamous cell carcinoma
10.3389/fgene.2020.583085 · 2021 · External reference
The peritumor microenvironment: physics and immunity
10.1016/j.trecan.2023.04.004 · 2023 · External reference
Treatment of locally advanced esophageal carcinoma: ASCO guideline
10.1200/jco.20.00866 · 2020 · External reference
Comparison of CT- and MRI-based quantification of tumor heterogeneity and vascularity for correlations with prognostic biomarkers and survival outcomes: a single-center prospective cohort study
10.3390/bioengineering10050504 · 2023 · External reference
Quantitative parameters derived from dual-energy computed tomography for the preoperative prediction of early recurrence in patients with esophageal squamous cell carcinoma
10.1007/s00330-023-09818-3 · 2023 · External reference
Sub-region based radiomics analysis for survival prediction in oesophageal tumours treated by definitive concurrent chemoradiotherapy
10.1016/j.ebiom.2019.05.023 · 2019 · External reference
Survival outcome prediction of esophageal squamous cell carcinoma patients based on radiomics and mutation signature
10.1186/s40644-024-00821-5 · 2025 · External reference
CT radiomics to predict pathologic complete response after neoadjuvant immunotherapy plus chemoradiotherapy in locally advanced esophageal squamous cell carcinoma
10.1007/s00330-024-11141-4 · 2025 · External reference
A nomogram integrating machine learning-derived CT radiomics and clinical characteristics for prognostic assessment in patients with locally advanced esophageal squamous cell carcinoma treated with definitive chemoradiotherapy with or without immunotherapy
10.1186/s12967-025-07387-1 · 2025 · External reference
Intratumoral and peritumoral heterogeneity based on CT to predict the pathological response after neoadjuvant chemoimmunotherapy in esophageal squamous cell carcinoma
10.1097/js9.0000000000003422 · 2026 · External reference
Decoding tumor stage by peritumoral and intratumoral radiomics in resectable esophageal squamous cell carcinoma
10.1007/s00261-023-04061-2 · 2024 · External reference
Comparison of the prognostic difference between ypTNM and equivalent pTNM stages in esophageal squamous cell carcinoma based on the 8th edition of AJCC classification
10.7150/jca.34567 · 2020 · External reference
Prognostic value of inflammatory markers and clinical features for survival in advanced or metastatic esophageal squamous cell carcinoma patients receiving anti-programmed death 1 treatment
10.3389/fonc.2023.1144875 · 2023 · External reference
Computed tomography-based intratumor heterogeneity predicts response to immunotherapy plus chemotherapy in esophageal squamous cell carcinoma
10.1016/j.acra.2024.06.032 · 2024 · External reference
A transfer learning approach on MRI-based radiomics signature for overall survival prediction of low-grade and high-grade gliomas
10.1007/s11517-023-02875-2 · 2023 · External reference
Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis
10.1016/j.aap.2019.105405 · 2020 · External reference
Hematoma expansion prediction: still navigating the intersection of deep learning and radiomics
10.1007/s00330-024-10586-x · 2024 · External reference
Comparison of machine learning algorithms for automatic prediction of Alzheimer disease
10.1097/jcma.0000000000001188 · 2025 · External reference
Detection of road extraction from satellite images with deep learning method
10.1007/s10586-024-04880-y · 2025 · External reference
Explainability-aligned reliability-weighted fuzzy ensemble for automated cervical cancer classification
10.1155/int/2931556 · 2026 · External reference
Neutrophils in cancer: neutral no more
10.1038/nrc.2016.52 · 2016 · External reference
Tumor-associated macrophage polarization promotes the progression of esophageal carcinoma
10.18632/aging.202201 · 2020 · External reference
Neutrophils in the activation and regulation of innate and adaptive immunity
10.1038/nri3024 · 2011 · External reference
Do alkaline phosphatases have great potential in the diagnosis, prognosis, and treatment of tumors
10.21037/tcr-23-1190 · 2023 · External reference
Metabolism score and machine learning models for the prediction of esophageal squamous cell carcinoma progression
10.1111/cas.16279 · 2024 · External reference
Radiomics: the bridge between medical imaging and personalized medicine
10.1038/nrclinonc.2017.141 · 2017 · External reference
Multiparametric MRI-based intratumoral and peritumoral radiomics for predicting the pathological differentiation of hepatocellular carcinoma
10.1186/s13244-024-01623-w · 2024 · External reference
Machine learning-based computational models derived from large-scale radiographic-radiomic images can help predict adverse histopathological status of gastric cancer
10.14309/ctg.0000000000000079 · 2019 · External reference
Intratumoral and peritumoral radiomics for forecasting microsatellite status in gastric cancer: a multicenter study
10.1186/s12885-025-13450-3 · 2025 · External reference
Multi-parametric MRI-based peritumoral radiomics on prediction of lymph-vascular space invasion in early-stage cervical cancer
10.5152/dir.2022.20657 · 2022 · External reference
Predicting microvascular invasion in small (≤5 cm) hepatocellular carcinomas using radiomics-based peritumoral analysis
10.1186/s13244-024-01649-0 · 2024 · External reference
Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma
10.1016/j.jhep.2019.02.023 · 2019 · External reference