Relation extraction for colorectal cancer via deep learning with entity-aware feature orthogonal decomposition
Relation extraction is significant for text structuring of colorectal cancer (CRC) pathological reports to facilitate doctors’ disease diagnoses. Although many relation extraction methods have been extensively studied for various natural language processing applications, they cannot be well transfer...
Saved in:
| Published in: | Expert systems with applications Vol. 258; p. 125188 |
|---|---|
| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
15.12.2024
|
| Subjects: | |
| ISSN: | 0957-4174 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Relation extraction is significant for text structuring of colorectal cancer (CRC) pathological reports to facilitate doctors’ disease diagnoses. Although many relation extraction methods have been extensively studied for various natural language processing applications, they cannot be well transferred to be applied for CRC pathological reports since CRC pathological reports have some unique characteristics. To this end, a deep learning framework is designed in this paper to extract entity relations in CRC pathological reports, which is based on an encoder–decoder architecture with entity-aware feature orthogonal decomposition. Specifically, to effectively extract semantic features of long and short entities, a two-stream encoder is designed based on an edge-aware convolutional neural network and a dimension-aware dilated convolution residual network. To alleviate the influence of the blending of subject–object features, entity-aware feature orthogonal decomposition is designed to decompose the extracted semantic features into three types, i.e. subject features, object features and subject–object shared features. A stage-wise cross entropy loss is proposed to well train the network. Comparison experiments indicated that our designed network performs well on CRC pathological texts with the performance of 92.3% F1 score, 93.1% Precision, and 91.5% Recall, outperforming the existing relation extraction models.
[Display omitted]
•Joint relation extraction for CRC pathological reports via deep learning.•Edge-aware CNNs and dimension-aware DCRN for extracting entity features.•Entity-aware feature orthogonal decomposition for decomposing entity features.•Stage-wise cross-entropy loss is proposed to well ensure the network training.•Perform well on real CRC pathological reports with the 92.3% F1 score. |
|---|---|
| AbstractList | Relation extraction is significant for text structuring of colorectal cancer (CRC) pathological reports to facilitate doctors’ disease diagnoses. Although many relation extraction methods have been extensively studied for various natural language processing applications, they cannot be well transferred to be applied for CRC pathological reports since CRC pathological reports have some unique characteristics. To this end, a deep learning framework is designed in this paper to extract entity relations in CRC pathological reports, which is based on an encoder–decoder architecture with entity-aware feature orthogonal decomposition. Specifically, to effectively extract semantic features of long and short entities, a two-stream encoder is designed based on an edge-aware convolutional neural network and a dimension-aware dilated convolution residual network. To alleviate the influence of the blending of subject–object features, entity-aware feature orthogonal decomposition is designed to decompose the extracted semantic features into three types, i.e. subject features, object features and subject–object shared features. A stage-wise cross entropy loss is proposed to well train the network. Comparison experiments indicated that our designed network performs well on CRC pathological texts with the performance of 92.3% F1 score, 93.1% Precision, and 91.5% Recall, outperforming the existing relation extraction models.
[Display omitted]
•Joint relation extraction for CRC pathological reports via deep learning.•Edge-aware CNNs and dimension-aware DCRN for extracting entity features.•Entity-aware feature orthogonal decomposition for decomposing entity features.•Stage-wise cross-entropy loss is proposed to well ensure the network training.•Perform well on real CRC pathological reports with the 92.3% F1 score. |
| ArticleNumber | 125188 |
| Author | Cai, Nian Chen, Chuanwen Feng, Jianjun Peng, Fuqiang Wang, Xiaodan Luo, Zhihao Li, Quanqing Liao, Jiacheng |
| Author_xml | – sequence: 1 givenname: Zhihao surname: Luo fullname: Luo, Zhihao email: 2112203076@mail2.gdut.edu.cn organization: School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China – sequence: 2 givenname: Jianjun orcidid: 0009-0002-8068-2138 surname: Feng fullname: Feng, Jianjun email: 3122002009@mail2.gdut.edu.cn organization: School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China – sequence: 3 givenname: Nian orcidid: 0000-0002-7826-5055 surname: Cai fullname: Cai, Nian email: cainian@gdut.edu.cn organization: School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China – sequence: 4 givenname: Xiaodan surname: Wang fullname: Wang, Xiaodan email: wangxiaodan@huayinlab.com organization: Guangzhou Huayinkang Medical Group Co., Ltd., Guangzhou 510006, China – sequence: 5 givenname: Jiacheng surname: Liao fullname: Liao, Jiacheng email: liaojiacheng@talkiin.cn organization: Foshan Talkiin Technology Co., LTD., 5th Floor, Building 1, Wanbang Commercial Plaza, Daliang Street, Shunde District, Foshan City, China – sequence: 6 givenname: Quanqing surname: Li fullname: Li, Quanqing email: liquanqing@huayinlab.com organization: Guangzhou Huayinkang Medical Group Co., Ltd., Guangzhou 510006, China – sequence: 7 givenname: Fuqiang orcidid: 0009-0003-6138-6883 surname: Peng fullname: Peng, Fuqiang email: pengfuqiang@huayinlab.com organization: Guangzhou Huayinkang Medical Group Co., Ltd., Guangzhou 510006, China – sequence: 8 givenname: Chuanwen surname: Chen fullname: Chen, Chuanwen email: chenchuanwen@huayinlab.com organization: Guangzhou Huayinkang Medical Group Co., Ltd., Guangzhou 510006, China |
| BookMark | eNp9kMtqwzAQRbVIoUnaH-hKP2BXku3YgW5K6AsChdKuhTweJQqOFCQ1af6-ctJVF4GBOwycgXsmZGSdRULuOMs547P7TY7hoHLBRJlzUfGmGZExm1d1VvK6vCaTEDaM8ZqxekzsB_YqGmcp_kSv4LRq5ym43nmEqHoKygJ6ujeKdog72qPy1tgVPZi4pmijicdMHZRHqlHF75TOx7VbOZvoDsFtdy6Y4fUNudKqD3j7l1Py9fz0uXjNlu8vb4vHZQYFYzETJYqiAAaCNTADUXYCuGC6bjkvuG5w3rWo06QzLyrQHdblrKiqds7bBupiSprzX_AuBI9agomnnqmk6SVncnAlN3JwJQdX8uwqoeIfuvNmq_zxMvRwhjCV2hv0MoDBpK0zg0TZOXMJ_wWdkYqk |
| CitedBy_id | crossref_primary_10_1016_j_eswa_2025_128207 |
| Cites_doi | 10.1016/j.cgh.2018.09.040 10.1590/S0041-87812001000100005 10.1016/j.knosys.2021.106888 10.1109/ACCESS.2020.2995739 10.1186/s12885-020-06766-9 10.1186/s12889-022-14274-7 10.1016/j.compeleceng.2021.107019 10.3390/curroncol28060447 10.1007/s40747-023-01004-8 10.1136/flgastro-2015-100565 10.3390/app13074447 10.1109/ICCV.2019.00041 10.1093/pubmed/fdad223 10.1016/j.jbi.2013.09.007 10.1136/amiajnl-2013-001628 10.1093/bioinformatics/bti268 10.1016/j.jbi.2019.103289 10.1038/s41575-023-00841-9 10.1186/1471-2105-9-207 10.1109/CVPR.2018.00745 10.1609/aaai.v36i10.21379 10.1001/jama.2010.1525 10.1145/3488560.3498409 10.1371/journal.pone.0200699 10.1093/jamia/ocu036 10.1016/j.eswa.2023.120441 10.1109/ACCESS.2023.3331504 |
| ContentType | Journal Article |
| Copyright | 2024 Elsevier Ltd |
| Copyright_xml | – notice: 2024 Elsevier Ltd |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.eswa.2024.125188 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| ExternalDocumentID | 10_1016_j_eswa_2024_125188 S0957417424020554 |
| GroupedDBID | --K --M .DC .~1 0R~ 13V 1B1 1RT 1~. 1~5 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN 9JO AAAKF AABNK AACTN AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AARIN AAXKI AAXUO AAYFN ABBOA ABFNM ABMAC ABMVD ABUCO ACDAQ ACGFS ACHRH ACNTT ACRLP ACZNC ADBBV ADEZE ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGUMN AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJOXV AKRWK ALEQD ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM AXJTR BJAXD BKOJK BLXMC BNSAS CS3 DU5 EBS EFJIC EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HAMUX IHE J1W JJJVA KOM LG9 LY1 LY7 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 RIG ROL RPZ SDF SDG SDP SDS SES SEW SPC SPCBC SSB SSD SSL SST SSV SSZ T5K TN5 ~G- 29G 9DU AAAKG AAQXK AATTM AAYWO AAYXX ABJNI ABKBG ABUFD ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADJOM ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS EFLBG EJD FEDTE FGOYB G-2 HLZ HVGLF HZ~ R2- SBC SET WUQ XPP ZMT ~HD |
| ID | FETCH-LOGICAL-c300t-24e233c0c208c6c24d2c120f7b1131f8e9dbefbef2c1135cfde746355b91b8c73 |
| ISICitedReferencesCount | 1 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001302114700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0957-4174 |
| IngestDate | Sat Nov 29 03:07:43 EST 2025 Tue Nov 18 21:40:59 EST 2025 Sat Sep 14 18:01:07 EDT 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Relation extraction Feature orthogonal decomposition Two-stream feature extraction Pathological reports Stage-wise cross entropy Colorectal cancer |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c300t-24e233c0c208c6c24d2c120f7b1131f8e9dbefbef2c1135cfde746355b91b8c73 |
| ORCID | 0000-0002-7826-5055 0009-0003-6138-6883 0009-0002-8068-2138 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_eswa_2024_125188 crossref_primary_10_1016_j_eswa_2024_125188 elsevier_sciencedirect_doi_10_1016_j_eswa_2024_125188 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-12-15 |
| PublicationDateYYYYMMDD | 2024-12-15 |
| PublicationDate_xml | – month: 12 year: 2024 text: 2024-12-15 day: 15 |
| PublicationDecade | 2020 |
| PublicationTitle | Expert systems with applications |
| PublicationYear | 2024 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Hanauer, Zheng (b11) 2015; 22 Zhang, Hu, Zhang, Liu (b39) 2023; 9 Sahu, Anand, Oruganty, Gattu (b25) 2016 Bhasuran, Natarajan (b3) 2018; 13 Zhang, Yang, Liu, Hu (b41) 2023; 13 Hu, J., Shen, L., & Sun, G. (2018). Squeeze-and-excitation networks. In Van der Maaten, Hinton (b31) 2008; 9 Yin, Mou, Xiong, Ren (b37) 2019; 98 Tang, Chen, Qin, Huang, Zheng (b30) 2023; 229 Wang, Y., Ma, X., Chen, Z., Luo, Y., Yi, J., & Bailey, J. (2019). Symmetric cross entropy for robust learning with noisy labels. In Bovée, Bloem, Flanagan, Nielsen, Yoshida (b4) 2020 Loshchilov, Hutter (b16) 2017 (pp. 7132–7141). Jelier, Jenster, Dorssers, van der Eijk, van Mulligen, Mons (b14) 2005; 21 Murphy, Zaki (b19) 2024; 21 Zhao, Yang, Qu, Xu, Li (b43) 2022; 35 Egner (b10) 2010; 304 Neilson, Rutter, Saunders, Plumb, Rees (b20) 2015; 6 (pp. 11285–11293). Liu, Wei, Jia, Vosoughi (b15) 2021 Siegel, Giaquinto, Jemal (b27) 2024; 74 Miao, Zhang, Zhang, Meng, Yu (b18) 2012 Wu, Bai, Yang, Wang, Tian (b36) 2021; 58 In Zhao, Xu, Cheng, Li, Gao (b42) 2021; 219 Araujo, Alves, Habr-Gama (b1) 2001; 56 Zaheer, Guruganesh, Dubey, Ainslie, Alberti, Ontanon (b38) 2020; 33 Rex, Shaukat, Wallace (b23) 2019; 17 Chopra, Hadsell, LeCun (b8) 2005; Vol. 1 Zhang, Li, Zhang (b40) 2020; 8 Ren, F., Zhang, L., Zhao, X., Yin, S., Liu, S., & Li, B. (2022). A simple but effective bidirectional framework for relational triple extraction. In Sun, Rumshisky, Uzuner (b28) 2013; 20 Saad El Din, Loree, Sayre, Gill, Brown, Dau (b24) 2020; 20 Wang, Yu, Zhang, Liu, Zhu, Sun (b34) 2020 Wan, Wan (b32) 2023 (pp. 322–330). Zheng, Wen, Chen, Yang, Zhang, Zhang (b45) 2021 Bundschus, Dejori, Stetter, Tresp, Kriegel (b5) 2008; 9 Mahulae, Silangen, Pongoh, Rampengan, Makahinda, Pomalingo (b17) 2024; 46 Sun, Xing, Zhang, Cai, Guo (b29) 2023; 11 Wei, Su, Wang, Tian, Chang (b35) 2019 Barresi, Bonetti, Leni, Caruso, Tuccari (b2) 2015 Shang, Y.-M., Huang, H., & Mao, X. (2022). Onerel: Joint entity and relation extraction with one module in one step. Eberts, Ulges (b9) 2020 Hu, Liu, Wang, Wu, Zhang, Liu (b12) 2021; 91 (pp. 824–832). Chang, Dai, Wu, Chen, Tsai, Hsu (b6) 2013; 46 Chen, Collins, Wang, Toh (b7) 2021; 28 Pan, Zhao, Deng, Zheng, Huang, Huang (b21) 2022; 22 Zheng, Wang, Bao, Hao, Zhou, Xu (b44) 2017 Miao (10.1016/j.eswa.2024.125188_b18) 2012 Murphy (10.1016/j.eswa.2024.125188_b19) 2024; 21 Jelier (10.1016/j.eswa.2024.125188_b14) 2005; 21 Liu (10.1016/j.eswa.2024.125188_b15) 2021 Zheng (10.1016/j.eswa.2024.125188_b45) 2021 Siegel (10.1016/j.eswa.2024.125188_b27) 2024; 74 Wei (10.1016/j.eswa.2024.125188_b35) 2019 Wu (10.1016/j.eswa.2024.125188_b36) 2021; 58 Egner (10.1016/j.eswa.2024.125188_b10) 2010; 304 Sahu (10.1016/j.eswa.2024.125188_b25) 2016 Bundschus (10.1016/j.eswa.2024.125188_b5) 2008; 9 10.1016/j.eswa.2024.125188_b33 Hanauer (10.1016/j.eswa.2024.125188_b11) 2015; 22 Wan (10.1016/j.eswa.2024.125188_b32) 2023 10.1016/j.eswa.2024.125188_b13 Mahulae (10.1016/j.eswa.2024.125188_b17) 2024; 46 Zhao (10.1016/j.eswa.2024.125188_b43) 2022; 35 Sun (10.1016/j.eswa.2024.125188_b29) 2023; 11 Zhang (10.1016/j.eswa.2024.125188_b40) 2020; 8 Van der Maaten (10.1016/j.eswa.2024.125188_b31) 2008; 9 Neilson (10.1016/j.eswa.2024.125188_b20) 2015; 6 Saad El Din (10.1016/j.eswa.2024.125188_b24) 2020; 20 Chang (10.1016/j.eswa.2024.125188_b6) 2013; 46 Chopra (10.1016/j.eswa.2024.125188_b8) 2005; Vol. 1 Barresi (10.1016/j.eswa.2024.125188_b2) 2015 Yin (10.1016/j.eswa.2024.125188_b37) 2019; 98 Bhasuran (10.1016/j.eswa.2024.125188_b3) 2018; 13 Pan (10.1016/j.eswa.2024.125188_b21) 2022; 22 Rex (10.1016/j.eswa.2024.125188_b23) 2019; 17 10.1016/j.eswa.2024.125188_b26 Chen (10.1016/j.eswa.2024.125188_b7) 2021; 28 10.1016/j.eswa.2024.125188_b22 Zaheer (10.1016/j.eswa.2024.125188_b38) 2020; 33 Sun (10.1016/j.eswa.2024.125188_b28) 2013; 20 Wang (10.1016/j.eswa.2024.125188_b34) 2020 Zheng (10.1016/j.eswa.2024.125188_b44) 2017 Araujo (10.1016/j.eswa.2024.125188_b1) 2001; 56 Zhang (10.1016/j.eswa.2024.125188_b39) 2023; 9 Zhang (10.1016/j.eswa.2024.125188_b41) 2023; 13 Bovée (10.1016/j.eswa.2024.125188_b4) 2020 Tang (10.1016/j.eswa.2024.125188_b30) 2023; 229 Hu (10.1016/j.eswa.2024.125188_b12) 2021; 91 Loshchilov (10.1016/j.eswa.2024.125188_b16) 2017 Eberts (10.1016/j.eswa.2024.125188_b9) 2020 Zhao (10.1016/j.eswa.2024.125188_b42) 2021; 219 |
| References_xml | – volume: 9 start-page: 1 year: 2008 end-page: 14 ident: b5 article-title: Extraction of semantic biomedical relations from text using conditional random fields publication-title: BMC Bioinformatics – volume: 21 start-page: 2049 year: 2005 end-page: 2058 ident: b14 article-title: Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes publication-title: Bioinformatics – volume: 9 start-page: 5235 year: 2023 end-page: 5250 ident: b39 article-title: NEDORT: a novel and efficient approach to the data overlap problem in relational triples publication-title: Complex & Intelligent Systems – volume: 13 start-page: 4447 year: 2023 ident: b41 article-title: BTDM: A bi-directional translating decoding model-based relational triple extraction publication-title: Applied Sciences – volume: 22 start-page: e219 year: 2015 end-page: e220 ident: b11 article-title: Paper versus EHR: simplistic comparisons may not capture current reality publication-title: Journal of the American Medical Informatics Association – start-page: 99 year: 2012 end-page: 107 ident: b18 article-title: Extracting and visualizing semantic relationships from Chinese biomedical text publication-title: Proceedings of the 26th Pacific Asia conference on language, information and computation – year: 2020 ident: b4 article-title: WHO classification of tumours editorial board publication-title: Soft tissue and bone tumours – reference: (pp. 824–832). – volume: 58 start-page: 513 year: 2021 end-page: 527 ident: b36 article-title: Review on text mining of electronic medical record publication-title: Journal of Computer Research and Development – year: 2020 ident: b34 article-title: TPLinker: Single-stage joint extraction of entities and relations through token pair linking – volume: 22 start-page: 1896 year: 2022 ident: b21 article-title: The global, regional, and national early-onset colorectal cancer burden and trends from 1990 to 2019: results from the global burden of disease study 2019 publication-title: BMC Public Health – volume: 229 year: 2023 ident: b30 article-title: Boundary regression model for joint entity and relation extraction publication-title: Expert Systems with Applications – year: 2021 ident: b45 article-title: PRGC: Potential relation and global correspondence based joint relational triple extraction – reference: Shang, Y.-M., Huang, H., & Mao, X. (2022). Onerel: Joint entity and relation extraction with one module in one step. – reference: Hu, J., Shen, L., & Sun, G. (2018). Squeeze-and-excitation networks. In – year: 2015 ident: b2 article-title: Histological grading in colorectal cancer: new insights and perspectives – volume: 9 year: 2008 ident: b31 article-title: Visualizing data using t-SNE publication-title: Journal of Machine Learning Research – volume: 20 start-page: 806 year: 2013 end-page: 813 ident: b28 article-title: Evaluating temporal relations in clinical text: 2012 i2b2 challenge publication-title: Journal of the American Medical Informatics Association – volume: 46 start-page: S54 year: 2013 end-page: S62 ident: b6 article-title: TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries publication-title: Journal of Biomedical Informatics – reference: Wang, Y., Ma, X., Chen, Z., Luo, Y., Yi, J., & Bailey, J. (2019). Symmetric cross entropy for robust learning with noisy labels. In – volume: 91 year: 2021 ident: b12 article-title: An overlapping sequence tagging mechanism for symptoms and details extraction on Chinese medical records publication-title: Computers & Electrical Engineering – volume: 35 start-page: 7953 year: 2022 end-page: 7965 ident: b43 article-title: Exploring privileged features for relation extraction with contrastive student-teacher learning publication-title: IEEE Transactions on Knowledge and Data Engineering – volume: 98 year: 2019 ident: b37 article-title: Chinese clinical named entity recognition with radical-level feature and self-attention mechanism publication-title: Journal of Biomedical Informatics – year: 2017 ident: b16 article-title: Decoupled weight decay regularization – reference: Ren, F., Zhang, L., Zhao, X., Yin, S., Liu, S., & Li, B. (2022). A simple but effective bidirectional framework for relational triple extraction. In – volume: 21 start-page: 25 year: 2024 end-page: 34 ident: b19 article-title: Changing epidemiology of colorectal cancer—birth cohort effects and emerging risk factors publication-title: Nature Reviews Gastroenterology & Hepatology – volume: 74 start-page: 12 year: 2024 end-page: 49 ident: b27 article-title: Cancer statistics, 2024 publication-title: CA: A Cancer Journal for Clinicians – volume: 56 start-page: 25 year: 2001 end-page: 35 ident: b1 article-title: Role of colonoscopy in colorectal cancer publication-title: Revista do Hospital das Clínicas – volume: 304 start-page: 1726 year: 2010 end-page: 1727 ident: b10 article-title: AJCC cancer staging manual publication-title: Jama – volume: 33 start-page: 17283 year: 2020 end-page: 17297 ident: b38 article-title: Big bird: Transformers for longer sequences publication-title: Advances in Neural Information Processing Systems – year: 2019 ident: b35 article-title: A novel cascade binary tagging framework for relational triple extraction – start-page: 1212 year: 2023 end-page: 1217 ident: b32 article-title: Entity relationship extraction for Chinese electronic medical records based on tightly cascaded binary pointers publication-title: 2023 IEEE 6th international conference on pattern recognition and artificial intelligence – volume: 8 start-page: 95947 year: 2020 end-page: 95955 ident: b40 article-title: Disease-pertinent knowledge extraction in online health communities using GRU based on a double attention mechanism publication-title: IEEE Access – year: 2021 ident: b15 article-title: Modulating language models with emotions – reference: (pp. 11285–11293). – reference: (pp. 322–330). – year: 2016 ident: b25 article-title: Relation extraction from clinical texts using domain invariant convolutional neural network – volume: 28 start-page: 5356 year: 2021 end-page: 5383 ident: b7 article-title: Pathological features and prognostication in colorectal cancer publication-title: Current Oncology – reference: (pp. 7132–7141). – volume: 11 start-page: 127422 year: 2023 end-page: 127430 ident: b29 article-title: Joint biomedical entity and relation extraction based on feature filter table labeling publication-title: IEEE Access – volume: 20 start-page: 1 year: 2020 end-page: 14 ident: b24 article-title: Trends in the epidemiology of young-onset colorectal cancer: a worldwide systematic review publication-title: BMC Cancer – volume: 219 year: 2021 ident: b42 article-title: Representation iterative fusion based on heterogeneous graph neural network for joint entity and relation extraction publication-title: Knowledge-Based Systems – reference: , In – volume: 17 start-page: 1428 year: 2019 end-page: 1437 ident: b23 article-title: Optimal management of malignant polyps, from endoscopic assessment and resection to decisions about surgery publication-title: Clinical Gastroenterology and Hepatology – start-page: 2006 year: 2020 end-page: 2013 ident: b9 article-title: Span-based joint entity and relation extraction with transformer pre-training publication-title: ECAI 2020 – volume: 46 start-page: e226 year: 2024 end-page: e227 ident: b17 article-title: Addressing the global challenge of colorectal cancer: recent trends and strategies for prevention publication-title: Journal of Public Health – year: 2017 ident: b44 article-title: Joint extraction of entities and relations based on a novel tagging scheme – volume: 13 year: 2018 ident: b3 article-title: Automatic extraction of gene-disease associations from literature using joint ensemble learning publication-title: PLoS One – volume: Vol. 1 start-page: 539 year: 2005 end-page: 546 ident: b8 article-title: Learning a similarity metric discriminatively, with application to face verification publication-title: 2005 IEEE computer society conference on computer vision and pattern recognition – volume: 6 start-page: 117 year: 2015 end-page: 126 ident: b20 article-title: Assessment and management of the malignant colorectal polyp publication-title: Frontline Gastroenterology – volume: 17 start-page: 1428 issue: 8 year: 2019 ident: 10.1016/j.eswa.2024.125188_b23 article-title: Optimal management of malignant polyps, from endoscopic assessment and resection to decisions about surgery publication-title: Clinical Gastroenterology and Hepatology doi: 10.1016/j.cgh.2018.09.040 – volume: 56 start-page: 25 year: 2001 ident: 10.1016/j.eswa.2024.125188_b1 article-title: Role of colonoscopy in colorectal cancer publication-title: Revista do Hospital das Clínicas doi: 10.1590/S0041-87812001000100005 – volume: 9 issue: 11 year: 2008 ident: 10.1016/j.eswa.2024.125188_b31 article-title: Visualizing data using t-SNE publication-title: Journal of Machine Learning Research – year: 2021 ident: 10.1016/j.eswa.2024.125188_b45 – volume: 219 year: 2021 ident: 10.1016/j.eswa.2024.125188_b42 article-title: Representation iterative fusion based on heterogeneous graph neural network for joint entity and relation extraction publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2021.106888 – volume: 8 start-page: 95947 year: 2020 ident: 10.1016/j.eswa.2024.125188_b40 article-title: Disease-pertinent knowledge extraction in online health communities using GRU based on a double attention mechanism publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2995739 – volume: 20 start-page: 1 year: 2020 ident: 10.1016/j.eswa.2024.125188_b24 article-title: Trends in the epidemiology of young-onset colorectal cancer: a worldwide systematic review publication-title: BMC Cancer doi: 10.1186/s12885-020-06766-9 – year: 2015 ident: 10.1016/j.eswa.2024.125188_b2 – start-page: 99 year: 2012 ident: 10.1016/j.eswa.2024.125188_b18 article-title: Extracting and visualizing semantic relationships from Chinese biomedical text – year: 2020 ident: 10.1016/j.eswa.2024.125188_b4 article-title: WHO classification of tumours editorial board – volume: 22 start-page: 1896 issue: 1 year: 2022 ident: 10.1016/j.eswa.2024.125188_b21 article-title: The global, regional, and national early-onset colorectal cancer burden and trends from 1990 to 2019: results from the global burden of disease study 2019 publication-title: BMC Public Health doi: 10.1186/s12889-022-14274-7 – start-page: 2006 year: 2020 ident: 10.1016/j.eswa.2024.125188_b9 article-title: Span-based joint entity and relation extraction with transformer pre-training – volume: 91 year: 2021 ident: 10.1016/j.eswa.2024.125188_b12 article-title: An overlapping sequence tagging mechanism for symptoms and details extraction on Chinese medical records publication-title: Computers & Electrical Engineering doi: 10.1016/j.compeleceng.2021.107019 – volume: 28 start-page: 5356 issue: 6 year: 2021 ident: 10.1016/j.eswa.2024.125188_b7 article-title: Pathological features and prognostication in colorectal cancer publication-title: Current Oncology doi: 10.3390/curroncol28060447 – volume: 9 start-page: 5235 issue: 5 year: 2023 ident: 10.1016/j.eswa.2024.125188_b39 article-title: NEDORT: a novel and efficient approach to the data overlap problem in relational triples publication-title: Complex & Intelligent Systems doi: 10.1007/s40747-023-01004-8 – volume: 6 start-page: 117 issue: 2 year: 2015 ident: 10.1016/j.eswa.2024.125188_b20 article-title: Assessment and management of the malignant colorectal polyp publication-title: Frontline Gastroenterology doi: 10.1136/flgastro-2015-100565 – year: 2020 ident: 10.1016/j.eswa.2024.125188_b34 – volume: 13 start-page: 4447 issue: 7 year: 2023 ident: 10.1016/j.eswa.2024.125188_b41 article-title: BTDM: A bi-directional translating decoding model-based relational triple extraction publication-title: Applied Sciences doi: 10.3390/app13074447 – ident: 10.1016/j.eswa.2024.125188_b33 doi: 10.1109/ICCV.2019.00041 – volume: 46 start-page: e226 issue: 1 year: 2024 ident: 10.1016/j.eswa.2024.125188_b17 article-title: Addressing the global challenge of colorectal cancer: recent trends and strategies for prevention publication-title: Journal of Public Health doi: 10.1093/pubmed/fdad223 – volume: 46 start-page: S54 year: 2013 ident: 10.1016/j.eswa.2024.125188_b6 article-title: TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries publication-title: Journal of Biomedical Informatics doi: 10.1016/j.jbi.2013.09.007 – volume: 20 start-page: 806 issue: 5 year: 2013 ident: 10.1016/j.eswa.2024.125188_b28 article-title: Evaluating temporal relations in clinical text: 2012 i2b2 challenge publication-title: Journal of the American Medical Informatics Association doi: 10.1136/amiajnl-2013-001628 – volume: 35 start-page: 7953 issue: 8 year: 2022 ident: 10.1016/j.eswa.2024.125188_b43 article-title: Exploring privileged features for relation extraction with contrastive student-teacher learning publication-title: IEEE Transactions on Knowledge and Data Engineering – volume: 21 start-page: 2049 issue: 9 year: 2005 ident: 10.1016/j.eswa.2024.125188_b14 article-title: Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti268 – volume: 98 year: 2019 ident: 10.1016/j.eswa.2024.125188_b37 article-title: Chinese clinical named entity recognition with radical-level feature and self-attention mechanism publication-title: Journal of Biomedical Informatics doi: 10.1016/j.jbi.2019.103289 – volume: 21 start-page: 25 issue: 1 year: 2024 ident: 10.1016/j.eswa.2024.125188_b19 article-title: Changing epidemiology of colorectal cancer—birth cohort effects and emerging risk factors publication-title: Nature Reviews Gastroenterology & Hepatology doi: 10.1038/s41575-023-00841-9 – volume: 9 start-page: 1 year: 2008 ident: 10.1016/j.eswa.2024.125188_b5 article-title: Extraction of semantic biomedical relations from text using conditional random fields publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-9-207 – ident: 10.1016/j.eswa.2024.125188_b13 doi: 10.1109/CVPR.2018.00745 – ident: 10.1016/j.eswa.2024.125188_b26 doi: 10.1609/aaai.v36i10.21379 – year: 2017 ident: 10.1016/j.eswa.2024.125188_b16 – start-page: 1212 year: 2023 ident: 10.1016/j.eswa.2024.125188_b32 article-title: Entity relationship extraction for Chinese electronic medical records based on tightly cascaded binary pointers – volume: 33 start-page: 17283 year: 2020 ident: 10.1016/j.eswa.2024.125188_b38 article-title: Big bird: Transformers for longer sequences publication-title: Advances in Neural Information Processing Systems – volume: 304 start-page: 1726 issue: 15 year: 2010 ident: 10.1016/j.eswa.2024.125188_b10 article-title: AJCC cancer staging manual publication-title: Jama doi: 10.1001/jama.2010.1525 – year: 2019 ident: 10.1016/j.eswa.2024.125188_b35 – year: 2021 ident: 10.1016/j.eswa.2024.125188_b15 – ident: 10.1016/j.eswa.2024.125188_b22 doi: 10.1145/3488560.3498409 – year: 2016 ident: 10.1016/j.eswa.2024.125188_b25 – volume: 13 issue: 7 year: 2018 ident: 10.1016/j.eswa.2024.125188_b3 article-title: Automatic extraction of gene-disease associations from literature using joint ensemble learning publication-title: PLoS One doi: 10.1371/journal.pone.0200699 – volume: 74 start-page: 12 issue: 1 year: 2024 ident: 10.1016/j.eswa.2024.125188_b27 article-title: Cancer statistics, 2024 publication-title: CA: A Cancer Journal for Clinicians – volume: 22 start-page: e219 issue: e1 year: 2015 ident: 10.1016/j.eswa.2024.125188_b11 article-title: Paper versus EHR: simplistic comparisons may not capture current reality publication-title: Journal of the American Medical Informatics Association doi: 10.1093/jamia/ocu036 – volume: 229 year: 2023 ident: 10.1016/j.eswa.2024.125188_b30 article-title: Boundary regression model for joint entity and relation extraction publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2023.120441 – year: 2017 ident: 10.1016/j.eswa.2024.125188_b44 – volume: 11 start-page: 127422 year: 2023 ident: 10.1016/j.eswa.2024.125188_b29 article-title: Joint biomedical entity and relation extraction based on feature filter table labeling publication-title: IEEE Access doi: 10.1109/ACCESS.2023.3331504 – volume: 58 start-page: 513 issue: 3 year: 2021 ident: 10.1016/j.eswa.2024.125188_b36 article-title: Review on text mining of electronic medical record publication-title: Journal of Computer Research and Development – volume: Vol. 1 start-page: 539 year: 2005 ident: 10.1016/j.eswa.2024.125188_b8 article-title: Learning a similarity metric discriminatively, with application to face verification |
| SSID | ssj0017007 |
| Score | 2.4566615 |
| Snippet | Relation extraction is significant for text structuring of colorectal cancer (CRC) pathological reports to facilitate doctors’ disease diagnoses. Although many... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 125188 |
| SubjectTerms | Colorectal cancer Feature orthogonal decomposition Pathological reports Relation extraction Stage-wise cross entropy Two-stream feature extraction |
| Title | Relation extraction for colorectal cancer via deep learning with entity-aware feature orthogonal decomposition |
| URI | https://dx.doi.org/10.1016/j.eswa.2024.125188 |
| Volume | 258 |
| WOSCitedRecordID | wos001302114700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: ScienceDirect database issn: 0957-4174 databaseCode: AIEXJ dateStart: 19950101 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0017007 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Nb9NAEF2FlgMXvlFLC9oDN8vV7trO2seqKiocIg5FRFws74dposqJ0iQt_4Ef3Rnvrp0UqOgBKbKikb2x_J4m49mZN4R8GKK5qFVcGGbhBYWbuEoqFptaZamyBU-ruh02IUejfDwuvgwGv0IvzPpSNk1-c1PM_yvUYAOwsXX2AXB3i4IBvgPocATY4fhPwIfytgjc7sJPAsdaQpSnRveGgiAI9SJaT6rIWDsPoyN8Vrbt3P0ZV9dYFFbbVvkzwu2d2Y82bWgs1qH7Yq-tzD7KJi-9OHRom9vYIO-Kf1Ztfvb7xeSimvWxqK8NBr5OVx1lT9y47NEGi7_5FPd4Us2MN_u8hWjVEV3nZpeAlHHK3Yye4IuF03H33hSDLzf07zdH73IO0yN7dY3qUSI96k_eVtW-82_X1SCG8rZpiWuUuEbp1nhEdoXMCvCRu8efTsefu10pyVz7fbhz34Tl6gXv3smfA52N4OX8OXnq3zrosWPLCzKwzUvyLEz0oN7BvyJNIA_tyUOBPLQnD3XkoUAeiuShgTwU8aab5KGePLQnD90iz2vy9ePp-clZ7CdyxDphbBmL1Iok0UwLluuhFqkRmgtWS8V5wuvcFkbZGj5g5kmma2NliiGtKrjKtUzekJ1m1tg9QlWlk6xSrFZcp1aLXEGsL_MMHubQSmb2CQ-Pr9Rerh6nplyWfwdun0TdNXMn1nLv2VlApfThpgsjSyDZPde9fdCvHJAnPfsPyc5ysbLvyGO9Xk6uFu89w24BHrKoOA |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Relation+extraction+for+colorectal+cancer+via+deep+learning+with+entity-aware+feature+orthogonal+decomposition&rft.jtitle=Expert+systems+with+applications&rft.au=Luo%2C+Zhihao&rft.au=Feng%2C+Jianjun&rft.au=Cai%2C+Nian&rft.au=Wang%2C+Xiaodan&rft.date=2024-12-15&rft.issn=0957-4174&rft.volume=258&rft.spage=125188&rft_id=info:doi/10.1016%2Fj.eswa.2024.125188&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_eswa_2024_125188 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0957-4174&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0957-4174&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0957-4174&client=summon |