Minning Zhao
Guangzhou, China
Last Updated: 09/26/2026
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Found 13 publications
Magnetic Resonance Imaging-Detected High-Risk Markers in Rectal Cancer Patients With a Pathologic Complete Response After Neoadjuvant Therapy.
Journal: JCO precision oncology
Published: December 10, 2025
Higher local recurrence as the distinct failure pattern in early-onset rectal cancer: a tailored MRI score to guide therapy.
Journal: NPJ precision oncology
Published: October 15, 2025
Correction: Artificial intelligence for quantifying immune infiltrates interacting with stroma in colorectal cancer.
Journal: Journal of translational medicine
Published: January 30, 2025
Prediction of Kirsten rat sarcoma (KRAS) mutation in rectal cancer with amide proton transfer-weighted magnetic resonance imaging.
Journal: Quantitative imaging in medicine and surgery
Published: February 20, 2024
Artificial intelligence-based analysis of tumor-infiltrating lymphocyte spatial distribution for colorectal cancer prognosis.
Journal: Chinese medical journal
Published: June 29, 2023
An MRI-based scoring system for pretreatment risk stratification in locally advanced rectal cancer.
Journal: British journal of cancer
Published: April 03, 2023
Artificial intelligence for quantifying immune infiltrates interacting with stroma in colorectal cancer.
Journal: Journal of translational medicine
Published: June 03, 2022
Combining Magnetic Resonance Diffusion-Weighted Imaging with Prostate-Specific Antigen to Differentiate Between Malignant and Benign Prostate Lesions.
Journal: Medical science monitor : international medical journal of experimental and clinical research
Published: April 23, 2022
Predicting Neoadjuvant Chemoradiotherapy Response in Locally Advanced Rectal Cancer Using Tumor-Infiltrating Lymphocytes Density.
Journal: Journal of inflammation research
Published: October 04, 2021
The Crohn's-like lymphoid reaction density: a new artificial intelligence quantified prognostic immune index in colon cancer.
Journal: Cancer immunology, immunotherapy : CII
Published: May 01, 2021
Cutoff points of T1 rho/T2 mapping relaxation times distinguishing early-stage and advanced osteoarthritis.
Journal: Archives of medical science : AMS
Published: April 29, 2021
Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images.
Journal: Precision clinical medicine
Published: December 25, 2020
Last Updated: 09/26/2026