In this task, systems are required to return, in addition to clinical code assignments (ICD-10-CM and ICD10-PCS codes), supporting evidence texts extracted from documents.
Se proporcionó una lista de códigos válidos para esta tarea con su descripción en inglés y español, que está disponible en https://zenodo.org/record/3706838.
Publication
Miranda-Escalada, A., Gonzalez-Agirre, A., Armengol-Estapé, J., Krallinger, M. (2020) Overview of automatic clinical coding: annotations, guidelines, and solutions for non-English clinical cases at CodiEsp track of eHealth CLEF 2020. In: CLEF (Working Notes)
Language
Spanish
NLP topic
Abstract task
Dataset
Year
2020
Publication link
Ranking metric
F1
Task results
| System | Precision | Recall | F1 Sort ascending | CEM | Accuracy | MacroPrecision | MacroRecall | MacroF1 | RMSE | MicroPrecision | MicroRecall | MicroF1 | MAE | MAP | UAS | LAS | MLAS | BLEX | Pearson correlation | Spearman correlation | MeasureC | BERTScore | EMR | Exact Match | F0.5 | Hierarchical F | ICM | MeasureC | Propensity F | Reliability | Sensitivity | Sentiment Graph F1 | WAC | b2 | erde30 | sent | weighted f1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FLE | 0.6870 | 0.5620 | 0.6110 | ||||||||||||||||||||||||||||||||||
| IAM | 0.7500 | 0.5240 | 0.6110 | ||||||||||||||||||||||||||||||||||
| Anuj | 0.5720 | 0.4560 | 0.5070 | ||||||||||||||||||||||||||||||||||
| The Mental Strokers | 0.5340 | 0.4780 | 0.5050 | ||||||||||||||||||||||||||||||||||
| UDC-UA | 0.6780 | 0.4920 | 0.4630 |
