Andu Zhang
Hebei Medical University(CN)Fourth Hospital of Hebei Medical University(CN)
Publications by Year
Research Areas
Esophageal Cancer Research and Treatment, Radiomics and Machine Learning in Medical Imaging, MRI in cancer diagnosis, Lung Cancer Diagnosis and Treatment, Gastric Cancer Management and Outcomes
Most-Cited Works
- → Investigation of Using Diffusion-Weighted Magnetic Resonance Imaging to Evaluate the Therapeutic Effect of Esophageal Carcinoma Treatment(2014)24 cited
- → Survival Comparision of Three-dimensional Radiotherapy Alone vs. Chemoradiotherapy for Esophageal Squamous Cell Carcinoma(2020)17 cited
- → Relationship between WBRT total dose, intracranial tumor control, and overall survival in NSCLC patients with brain metastases - a single-center retrospective analysis(2019)10 cited
- → Can lymphovascular invasion be predicted by contrast-enhanced CT imaging features in patients with esophageal squamous cell carcinoma? A preliminary retrospective study(2022)9 cited
- → Computed tomography radiomics identification of T1–2 and T3–4 stages of esophageal squamous cell carcinoma: two-dimensional or three-dimensional?(2023)6 cited
- → Predicting the effects of radiotherapy based on diffusion kurtosis imaging in a xenograft mouse model of esophageal carcinoma(2021)5 cited
- → Comparison of TNM AJCC/UICC 8th with JES 11th staging systems for prognostic prediction in patients with esophageal squamous cell carcinoma who underwent radical (chemo) radiotherapy in China(2023)5 cited
- → Comparative evaluation of imaging methods for prognosis assessment in esophageal squamous cell carcinoma: focus on diffusion-weighted magnetic resonance imaging, computed tomography and esophagography(2024)3 cited
- → RecurIndex-Guided postoperative radiotherapy with or without Avoidance of Irradiation of regional Nodes in 1–3 node-positive breast cancer (RIGAIN): a study protocol for a multicentre, open-label, randomised controlled prospective, phase III trial(2024)2 cited
- → Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients(2024)2 cited