Discovering Clinically Meaningful Shape Features for the Analysis of Tumor Pathology Images

1 code implementation • 9 Dec 2020 • Esteban Fernández Morales, Cong Zhang, Guanghua Xiao, Chul Moon, Qiwei Li

With the advanced imaging technology, digital pathology imaging of tumor tissue slides is becoming a routine clinical procedure for cancer diagnosis.

Using Persistent Homology Topological Features to Characterize Medical Images: Case Studies on Lung and Brain Cancers

1 code implementation • 7 Dec 2020 • Chul Moon, Qiwei Li, Guanghua Xiao

Tumor shape is a key factor that affects tumor growth and metastasis.

Bayesian Modeling of Microbiome Data for Differential Abundance Analysis

2 code implementations • 23 Feb 2019 • Qiwei Li, Shuang Jiang, Andrew Y. Koh, Guanghua Xiao, Xiaowei Zhan

To overcome these challenges, we propose a Bayesian hierarchical modeling framework for the analysis of microbiome count data for differential abundance analysis.

Methodology

A Bayesian Zero-Inflated Negative Binomial Regression Model for the Integrative Analysis of Microbiome Data

1 code implementation • 23 Dec 2018 • Shuang Jiang, Guanghua Xiao, Andrew Y. Koh, Qiwei Li, Xiaowei Zhan

Hence, we present an integrative Bayesian zero-inflated negative binomial regression model that can both distinguish differential abundant taxa with distinct phenotypes and quantify covariate-taxa effects.

Applications

A Bayesian Mark Interaction Model for Analysis of Tumor Pathology Images

1 code implementation • 22 Feb 2018 • Qiwei Li, Xinlei Wang, Faming Liang, Guanghua Xiao

This statistical methodology not only presents a new model for characterizing spatial correlations in a multi-type spatial point pattern, but also provides a new perspective for understanding the role of cell-cell interactions in cancer progression.

Methodology 62M30, 62F15