Name
Title | ||
|---|---|---|
Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text. |
Abstract | ||
|---|---|---|
•We propose a neural model for ICD-10 coding of text describing causes of death.•We describe the application to data from the Portuguese Ministry of Health.•The proposed model makes accurate predictions, outperforming simpler baselines.•We show accuracies of 89%, 81%, and 76%, for ICD chapters, blocks, and full-codes.•The model can produce interpretable results, useful for public health surveillance. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jbi.2018.02.011 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
Automated ICD coding,Clinical text mining,Deep learning,Natural language processing,Artificial intelligence in medicine | Christian ministry,Public health surveillance,Information retrieval,Computer science,Portuguese,Coding (social sciences),Initialization,Artificial neural network,ICD-10 | Journal |
Volume | ISSN | Citations |
80 | 1532-0464 | 3 |
PageRank | References | Authors |
0.47 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisco Duarte | 1 | 3 | 0.47 |
| Bruno Martins | 2 | 441 | 34.58 |
| Cátia Sousa Pinto | 3 | 3 | 0.47 |
| Mário J. Silva | 4 | 1166 | 103.66 |