Development of multiple AI pipelines that predict neoadjuvant chemotherapy response of breast cancer using H&E-stained tissues.

Authors:
Shen B; Saito A; Ueda A; Fujita K; Nagamatsu Y and 14 more

Journal:
J Pathol Clin Res

Publication Year: 2023

DOI:
10.1002/cjp2.314

PMCID:
PMC10073928

PMID:
36896856

Journal Information

Full Title: J Pathol Clin Res

Abbreviation: J Pathol Clin Res

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Pathology

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

Transparency Score
4/6
66.7% Transparent
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Data Sharing
Evidence found in paper:

"the self-developed algorithm cflcm used for this study is available at the following link: https://github com/shen-tokyomed/breast_ai_cflcm_tool ."

Evidence found in paper:

"No conflicts of interest were declared."

Evidence found in paper:

"This work was supported by grants from the JSPS KAKENHI grant numbers (17H04067 and 21H02706 to MK, 18K07027 to AS). This work was also supported in part by the Strategic Research Foundation Grant‐aided Project (S1511011) for Private Universities from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MK)."

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Open Access
Paper is freely available to read
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Assessment Info

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OST Version: N/A

Last Updated: Aug 05, 2025