A benchmark for comparing precision medicine methods in thyroid cancer diagnosis using tissue microarrays | Zendy

ChingWei Wang | Zendy; YuChing Lee | Zendy; Evelyne Calista | Zendy; Fan Zhou | Zendy; Hongtu Zhu | Zendy; Ryôhei Suzuki | Zendy; Daisuke Komura | Zendy; Shumpei Ishikawa | Zendy; ShihPing Cheng | Zendy

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A benchmark for comparing precision medicine methods in thyroid cancer diagnosis using tissue microarrays

Author(s) -

ChingWei Wang,

YuChing Lee,

Evelyne Calista,

Fan Zhou,

Hongtu Zhu,

Ryôhei Suzuki,

Daisuke Komura,

Shumpei Ishikawa,

ShihPing Cheng

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx838

Subject(s) - computer science , benchmark (surveying) , ranking (information retrieval) , thyroid cancer , machine learning , artificial intelligence , annotation , tissue microarray , software , data mining , cancer , medical physics , medicine , geodesy , programming language , geography

The aim of precision medicine is to harness new knowledge and technology to optimize the timing and targeting of interventions for maximal therapeutic benefit. This study explores the possibility of building AI models without precise pixel-level annotation in prediction of the tumor size, extrathyroidal extension, lymph node metastasis, cancer stage and BRAF mutation in thyroid cancer diagnosis, providing the patients' background information, histopathological and immunohistochemical tissue images.

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