Three papers accepted to the International Conference Recent Advances in Natural Language Processing, RANLP 2021, September 1-3, 2021 in Varna, Bulgaria,
from the Clinical Text Mining group at DSV:
Sonja Remmer, Anastasios Lamproudis and Hercules Dalianis.
Multi-label Diagnosis Classification of Swedish Discharge Summaries – ICD-10 Code Assignment Using KB-BERT.
Alberto Blanco, Sonja Remmer, Alicia Pérez, Hercules Dalianis and Arantza Casillas.
On the contribution of per-ICD attention mechanisms to classify health records in languages with fewer resources than English.
Anastasios Lamproudis, Aron Henriksson and Hercules Dalianis.
Developing a Clinical Language Model for Swedish: Continued Pretraining of Generic BERT with In-Domain Data.
The first paper in collaboration with the Norwegian Centre for E-health Research in Tromsø. Norway and the second paper also with the HiTZ Center – Ixa, University of the Basque Country UPV/EHU, Donostia, Spain.
The two first papers study how to automatically assign ICD-10 diagnosis codes to a discharge summary, for Swedish and for Spanish a respectively. Usually this time consuming work is carried out manually by a physician or a coder.We use machine learning and specifically Deep AI Learning to perform this and already manually assign codes to discharges summaries.
In the third paper is constructed a clinical deep learning BERT model for Swedish that performs much better than a regular non-clinical model for clinical down stream tasks as for example automatic ICD-10 diagnosis coding.