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  4. Artificial intelligence assisted determination of Tumor Proportion Score (TPS) in HNSCC patients
 
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Artificial intelligence assisted determination of Tumor Proportion Score (TPS) in HNSCC patients

Journal
Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Journal Volume
11627
Date Issued
2021
Author(s)
Tseng, Po-Hang
Liao, Xin-Yu
Lin, Jing-Tang
Lee, Sheng-Lin
MEI-CHUN LIN  
YEN-LIN HUANG  
PEI-JEN LOU  
CHEN-YUAN DONG  
DOI
10.1117/12.2583791
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108857973&doi=10.1117%2f12.2583791&partnerID=40&md5=4a3c358f0ab6954e852c3eb5c2bc2567
https://scholars.lib.ntu.edu.tw/handle/123456789/606469
Abstract
At the present, identifying head and neck squamous cell carcinoma (HNSCC) patients for immune checkpoint inhibitor therapy (ICIT) is achieved through the determination of Tumor Proportion Score (TPS) or the percentage of tumor cells positively labeled for PD-L1. Estimation of TPS is largely done in a manual fashion by a trained pathologist. In the case of HNSCC, the histological section can be over 1 cm in size in which over 100,000 cancer cells need to be evaluated for PD-L1 expression. To expedite the TPS evaluation process for such large specimens, we have developed a platform in which artificial intelligence (AI) is used for TPS determination. With additional development, this approach may be used in the clinical setting to assist pathologists in TPS evaluation. ? 2021 SPIE.
Subjects
Artificial intelligence; Cancer immunotherapy; Head and neck squamous cell carcinoma (HNSCC); Tumor proportion score; Dentistry; Diagnosis; Surgery; Tumors; Cancer cells; Clinical settings; Head-and-neck squamous cell carcinoma; Histological section; Manual fashion; Tumor cells; Artificial intelligence
SDGs

[SDGs]SDG3

Type
conference paper

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