Pathomic model based on histopathological features and machine learning to predict IDO1 status and its association with breast cancer prognosis.

Journal: Breast cancer research and treatment

PMID: 38780888

Abstract

PURPOSE: To establish a pathomic model using histopathological image features for predicting indoleamine 2,3-dioxygenase 1 (IDO1) status and its relationship with overall survival (OS) in breast cancer.

Authors

Xiaohua Zhuo

Department of Pathology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China.
Hailong Deng

Department of Pathology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China.
Mingzhu Qiu

Department of Pathology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, China.
Xiaoming Qiu

Dept of Radiology, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi, China.

Keywords

Biomarkers, Tumor Breast Neoplasms Female Gene Expression Regulation, Neoplastic Humans Indoleamine-Pyrrole 2,3,-Dioxygenase Kaplan-Meier Estimate Machine Learning Middle Aged Prognosis Tumor Microenvironment

External Resources

View on PubMed Access via DOI PubMed (38780888)

Pathomic model based on histopathological features and machine learning to predict IDO1 status and its association with breast cancer prognosis.

Abstract

Authors

Keywords

External Resources

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