Abstract
As a predominant threat to women's health world-wide, breast cancer has become increasingly important in on-cology research. The discovery of molecular subtypes of breast cancer has led to more subtype oriented treatment and prognosis prediction. Effective prognosis models help to estimate the recurrence as well as the quality and duration of survival, leading to more personalized treatments. However, most traditional prognostic models either ignore molecular subtypes or only make limited use of them. The roles of molecular subtypes in the development and treatment of breast cancer have not been fully revealed. With the over 1200 cases collected by Sir Run Run Shaw Hospital of Zhejiang University in the past two decades, we aim to improve understanding of molecular subtypes and their impacts on the prognosis via data analysis in the long run. As the initial stage, this short paper presents our preliminary work of logistic regression experiments with the data. Though molecular subtypes have not been included the tentative model, they are to be explored further in following stages.
Original language | English |
---|---|
Title of host publication | 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 363-366 |
Number of pages | 4 |
ISBN (Electronic) | 9781665484879 |
ISBN (Print) | 9781665484886 |
DOIs | |
Publication status | Published - 14 Nov 2022 |
Event | IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) - https://bibe2022.asia.edu.tw/, Taichung, Taiwan Duration: 7 Nov 2022 → 9 Nov 2022 https://bibe2022.asia.edu.tw/ |
Publication series
Name | 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) |
---|---|
Publisher | IEEE |
Conference
Conference | IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) |
---|---|
Abbreviated title | BIBE 2022 |
Country/Territory | Taiwan |
City | Taichung |
Period | 7/11/22 → 9/11/22 |
Internet address |
Keywords
- breast cancer
- prognostic models
- survival analysis
- logistic regression
- molecular subtypes