Health Card Retrieval for Consumer Health Search
Author:
Affiliation:
1. Univeristy of Queensland & University of Surabaya, Brisbane, Australia
2. Univeristy of Queensland, Brisbane, Australia
3. Australian E-Health Research Center, CSIRO, Brisbane, Australia
4. University of Queensland, Brisbane, Australia
Funder
Australian Research Council DECRA Research Fellowship
Indonesia Endowment Fund for Education (LPDP)
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3357384.3358128
Reference18 articles.
1. Beam AL Kompa B Fried I Palmer NP Shi X Cai T and Kohane IS. 2018. Clinical concept embeddings learned from massive sources of medical data. arXiv preprint arXiv:1804.01486 (2018). Beam AL Kompa B Fried I Palmer NP Shi X Cai T and Kohane IS. 2018. Clinical concept embeddings learned from massive sources of medical data. arXiv preprint arXiv:1804.01486 (2018).
2. Radlinski F Craswell N Billerbeck B Shokouhi M Ahari S Agrawal N Hoad T Zhou S and Awan MA. 2015. Entity detection and extraction for entity cards. US Patent 9 158 846. Radlinski F Craswell N Billerbeck B Shokouhi M Ahari S Agrawal N Hoad T Zhou S and Awan MA. 2015. Entity detection and extraction for entity cards. US Patent 9 158 846.
3. 2016. Quality versus efficiency in document scoring with learning-to-rank models;Capannini G;IP&M,2016
4. SIGIR 2018 Tutorial on Health Search (HS2018)
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