# Modified ResNet Model for MSI and MSS Classification of Gastrointestinal Cancer

arXiv: https://arxiv.org/abs/2202.01905 · HTML: https://mlsanity.com/paper/2202.01905/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 13 references that are in the map.
- First posted on arXiv 3 Feb 2022.

## Builds on (most cited first, 6 of 6)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [RCCNet: An Efficient Convolutional Neural Network for Histological Routine Colon Cancer Nuclei Classification](https://mlsanity.com/paper/1810.02797/) (2018)
- [Deep Learning Based Computer-Aided Systems for Breast Cancer Imaging : A Critical Review](https://mlsanity.com/paper/2010.00961/) (2020)
- [Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation](https://mlsanity.com/paper/2006.12285/) (2020)
- [Lung Cancer Detection and Classification based on Image Processing and Statistical Learning](https://mlsanity.com/paper/1911.10654/) (2019)

## Built on by (most cited first, 1 of 1)

- [Privacy-Preserving Deep Learning Model for Covid-19 Disease Detection](https://mlsanity.com/paper/2209.04445/) (2022)

## Abstract (arXiv)

In this work, a modified ResNet model is proposed for the classification of Microsatellite instability(MSI) and Microsatellite stability(MSS) of gastrointestinal cancer. The performance of this model is analyzed and compared with existing models. The proposed model surpassed the existing models with an accuracy of 0.8981 and F1 score of 0.9178.