Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66960, first published .
A Machine Learning–Based Scoring System to Identify High Immunoactivity Microsatellite Stability Tumors by Quantifying Similarity to Microsatellite Instability-High Tumors in Colorectal Cancers: Development and Quantitative Study

A Machine Learning–Based Scoring System to Identify High Immunoactivity Microsatellite Stability Tumors by Quantifying Similarity to Microsatellite Instability-High Tumors in Colorectal Cancers: Development and Quantitative Study

A Machine Learning–Based Scoring System to Identify High Immunoactivity Microsatellite Stability Tumors by Quantifying Similarity to Microsatellite Instability-High Tumors in Colorectal Cancers: Development and Quantitative Study

Hongkai Yan   1, 2, 3 * , MD ;   Li Jiang   4 * , Dr rer nat ;   Yaqi Li   1, 3 , MD, PhD ;   Fengchong Wang   5 , MSc ;   Shaobo Mo   1, 3 , MD, PhD ;   Weiqi Sheng   1, 6, 7 , MD, PhD ;   Dan Huang   1, 6, 7 * , MD, PhD ;   Junjie Peng   1, 3 * , MD, PhD

1 Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China

2 Department of Pediatric Cardiology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China

3 Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China

4 Weifang Key Laboratory of Collaborative Innovation of Intelligent Diagnosis and Treatment and Molecular Diseases, School of Basic Medical Sciences, Shandong Second Medical University, Weifang, China

5 Weifang Ten Nanometer Biotechnology Co., Ltd., Weifang, China

6 Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China

7 Institute of Pathology, Fudan University, Shanghai, China

*these authors contributed equally

Corresponding Author:

  • Junjie Peng, MD, PhD
  • Department of Colorectal Surgery
  • Fudan University Shanghai Cancer Center
  • 270 Dong’An Road
  • Shanghai 200032
  • China
  • Phone: 86 02164175590
  • Email: pengjj@shca.org.cn