HITSZ_CDR: An end-to-end chemical and disease relation extraction system for BioCreative V

Haodi Li; Buzhou Tang; Qingcai Chen; Kai Chen; Xiaolong Wang; Baohua Wang; Zhe Wang

doi:10.1093/database/baw077

HITSZ_CDR: An end-to-end chemical and disease relation extraction system for BioCreative V

Haodi Li
, Buzhou Tang^*
, Qingcai Chen
, Kai Chen
, Xiaolong Wang
, Baohua Wang
, Zhe Wang

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen
Jilin University
Shenzhen University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

In this article, an end-to-end system was proposed for the challenge task of disease named entity recognition (DNER) and chemical-induced disease (CID) relation extraction in BioCreative V, where DNER includes disease mention recognition (DMR) and normalization (DN). Evaluation on the challenge corpus showed that our system achieved the highest F1-scores 86.93% on DMR, 84.11% on DN, 43.04% on CID relation extraction, respectively. The F1-score on DMR is higher than our previous one reported by the challenge organizers (86.76%), the highest F1-score of the challenge.

Original language	English
Article number	baw077
Journal	Database : the journal of biological databases and curation
Volume	2016
DOIs	https://doi.org/10.1093/database/baw077
State	Published - 2016
Externally published	Yes

Access to Document

10.1093/database/baw077

Cite this

@article{616420f7eaae4d99bfa9cecaedd596f5,

title = "HITSZ\_CDR: An end-to-end chemical and disease relation extraction system for BioCreative V",

abstract = "In this article, an end-to-end system was proposed for the challenge task of disease named entity recognition (DNER) and chemical-induced disease (CID) relation extraction in BioCreative V, where DNER includes disease mention recognition (DMR) and normalization (DN). Evaluation on the challenge corpus showed that our system achieved the highest F1-scores 86.93\% on DMR, 84.11\% on DN, 43.04\% on CID relation extraction, respectively. The F1-score on DMR is higher than our previous one reported by the challenge organizers (86.76\%), the highest F1-score of the challenge.",

author = "Haodi Li and Buzhou Tang and Qingcai Chen and Kai Chen and Xiaolong Wang and Baohua Wang and Zhe Wang",

year = "2016",

doi = "10.1093/database/baw077",

language = "英语",

volume = "2016",

journal = "Database : the journal of biological databases and curation",

issn = "1758-0463",

publisher = "Oxford University Press",

}

TY - JOUR

T1 - HITSZ_CDR

T2 - An end-to-end chemical and disease relation extraction system for BioCreative V

AU - Li, Haodi

AU - Tang, Buzhou

AU - Chen, Qingcai

AU - Chen, Kai

AU - Wang, Xiaolong

AU - Wang, Baohua

AU - Wang, Zhe

PY - 2016

Y1 - 2016

N2 - In this article, an end-to-end system was proposed for the challenge task of disease named entity recognition (DNER) and chemical-induced disease (CID) relation extraction in BioCreative V, where DNER includes disease mention recognition (DMR) and normalization (DN). Evaluation on the challenge corpus showed that our system achieved the highest F1-scores 86.93% on DMR, 84.11% on DN, 43.04% on CID relation extraction, respectively. The F1-score on DMR is higher than our previous one reported by the challenge organizers (86.76%), the highest F1-score of the challenge.

AB - In this article, an end-to-end system was proposed for the challenge task of disease named entity recognition (DNER) and chemical-induced disease (CID) relation extraction in BioCreative V, where DNER includes disease mention recognition (DMR) and normalization (DN). Evaluation on the challenge corpus showed that our system achieved the highest F1-scores 86.93% on DMR, 84.11% on DN, 43.04% on CID relation extraction, respectively. The F1-score on DMR is higher than our previous one reported by the challenge organizers (86.76%), the highest F1-score of the challenge.

UR - https://www.scopus.com/pages/publications/85020322507

U2 - 10.1093/database/baw077

DO - 10.1093/database/baw077

M3 - 文章

C2 - 27270713

AN - SCOPUS:85020322507

SN - 1758-0463

VL - 2016

JO - Database : the journal of biological databases and curation

JF - Database : the journal of biological databases and curation

M1 - baw077

ER -

HITSZ_CDR: An end-to-end chemical and disease relation extraction system for BioCreative V

Abstract

Access to Document

Other files and links

Fingerprint

Cite this