Artificial intelligence modelling in differentiating core biopsies of fibroadenoma from phyllodes tu...
Artificial intelligence modelling in differentiating core biopsies of fibroadenoma from phyllodes tumor
About this item
Full title
Author / Creator
Cheng, Chee Leong , Md Nasir, Nur Diyana , Ng, Gary Jian Zhe , Chua, Kenny Wei Jie , Li, Yier , Rodrigues, Joshua , Thike, Aye Aye , Heng, Seow Ye , Koh, Valerie Cui Yun , Lim, Johnathan Xiande , Hiew, Venice Jing Ning , Shi, Ruoyu , Tan, Benjamin Yongcheng , Tay, Timothy Kwang Yong , Ravi, Sudha , Ng, Kim Hock , Oh, Kevin Seng Loong and Tan, Puay Hoon
Publisher
New York: Elsevier Inc
Journal title
Language
English
Formats
Publication information
Publisher
New York: Elsevier Inc
Subjects
More information
Scope and Contents
Contents
Breast fibroepithelial lesions (FEL) are biphasic tumors which consist of benign fibroadenomas (FAs) and the rarer phyllodes tumors (PTs). FAs and PTs have overlapping features, but have different clinical management, which makes correct core biopsy diagnosis important. This study used whole-slide images (WSIs) of 187 FA and 100 PT core biopsies, t...
Alternative Titles
Full title
Artificial intelligence modelling in differentiating core biopsies of fibroadenoma from phyllodes tumor
Authors, Artists and Contributors
Author / Creator
Md Nasir, Nur Diyana
Ng, Gary Jian Zhe
Chua, Kenny Wei Jie
Li, Yier
Rodrigues, Joshua
Thike, Aye Aye
Heng, Seow Ye
Koh, Valerie Cui Yun
Lim, Johnathan Xiande
Hiew, Venice Jing Ning
Shi, Ruoyu
Tan, Benjamin Yongcheng
Tay, Timothy Kwang Yong
Ravi, Sudha
Ng, Kim Hock
Oh, Kevin Seng Loong
Tan, Puay Hoon
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_miscellaneous_2602642062
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2602642062
Other Identifiers
ISSN
0023-6837
E-ISSN
1530-0307
DOI
10.1038/s41374-021-00689-0
