Jocelyn Dunstan

According to our database, Jocelyn Dunstan authored at least 22 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Physics-informed neural networks for blood flow inverse problems.

Jeremias Garay, Jocelyn Dunstan, Sergio Uribe, Francisco Sahli Costabal

CoRR, 2023

LinkMed: Entity Recognition and Relation Extraction from Clinical Notes in Spanish.

Carlos Muñoz-Castro, Andrés Carvallo, Matías Rojas, Claudio Aracena, Rodrigo Guerra, Benjamín Pizarro, Jocelyn Dunstan

Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2023) co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2023), 2023

CMM PLN at MentalRiskES: A Traditional Machine Learning Approach for Detection of Eating Disorders and Depression in Chat Messages.

Rodrigo Guerra, Benjamín Pizarro, Carlos Muñoz-Castro, Andrés Carvallo, Matías Rojas, Claudio Aracena, Jocelyn Dunstan

Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2023) co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2023), 2023

Automatic Section Classification in Spanish Clinical Narratives Using Chunked Named Entity Recognition.

Andrés Carvallo, Matías Rojas, Carlos Muñoz-Castro, Claudio Aracena, Rodrigo Guerra, Benjamín Pizarro, Jocelyn Dunstan

Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2023) co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2023), 2023

Development of pre-trained language models for clinical NLP in Spanish.

Claudio Aracena, Jocelyn Dunstan

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: EACL 2023, 2023

Automatic Coding at Scale: Design and Deployment of a Nationwide System for Normalizing Referrals in the Chilean Public Healthcare System.

Fabián Villena, Matías Rojas, Felipe Arias, Jorge Pacheco, Paulina Vera, Jocelyn Dunstan

Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023

Pre-trained language models in Spanish for health insurance coverage.

Claudio Aracena, Nicolás Rodríguez, Victor Rocco, Jocelyn Dunstan

Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023

2022

Automatic Extraction of Nested Entities in Clinical Referrals in Spanish.

Pablo Báez, Felipe Bravo-Marquez, Jocelyn Dunstan, Matías Rojas, Fabián Villena

ACM Trans. Comput. Heal., 2022

Training and intrinsic evaluation of lightweight word embeddings for the clinical domain in Spanish.

Carolina Chiu, Fabián Villena, Kinan Martin, Fredy Núñez, Cecilia Besa, Jocelyn Dunstan

Frontiers Artif. Intell., 2022

FLERT-Matcher: A Two-Step Approach for Clinical Named Entity Recognition and Normalization.

Matías Rojas, Jose Barros, Mauricio Araneda, Jocelyn Dunstan

Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2022) co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2022), 2022

PLN CMM at SocialDisNER: Improving Detection of Disease Mentions in Tweets by Using Document-Level Features.

Matías Rojas, Jose Barros, Kinan Martin, Mauricio Araneda-Hernandez, Jocelyn Dunstan

Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, 2022

Simple Yet Powerful: An Overlooked Architecture for Nested Named Entity Recognition.

Matías Rojas, Felipe Bravo-Marquez, Jocelyn Dunstan

Proceedings of the 29th International Conference on Computational Linguistics, 2022

Assessing the Limits of Straightforward Models for Nested Named Entity Recognition in Spanish Clinical Narratives.

Matías Rojas, Casimiro Pio Carrino, Aitor Gonzalez-Agirre, Jocelyn Dunstan, Marta Villegas

Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis, 2022

Divide and Conquer: An Extreme Multi-Label Classification Approach for Coding Diseases and Procedures in Spanish.

Jose Barros, Matías Rojas, Jocelyn Dunstan, Andrés Abeliuk

Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis, 2022

A Knowledge-Graph-Based Intrinsic Test for Benchmarking Medical Concept Embeddings and Pretrained Language Models.

Claudio Aracena, Fabián Villena, Matías Rojas, Jocelyn Dunstan

Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis, 2022

2021

Data Science for Engineers: A Teaching Ecosystem.

Felipe A. Tobar, Felipe Bravo-Marquez, Jocelyn Dunstan, Joaquín Fontbona, Alejandro Maass, Daniel Remenik, Jorge F. Silva

IEEE Signal Process. Mag., 2021

Correction to: Supporting the classification of patients in public hospitals in Chile by designing, deploying and validating a system based on natural language processing.

Fabián Villena, Jorge Pérez, René Lagos, Jocelyn Dunstan

BMC Medical Informatics Decis. Mak., 2021

Supporting the classification of patients in public hospitals in Chile by designing, deploying and validating a system based on natural language processing.

Jocelyn Dunstan, Fabián Villena, Jorge Pérez, René Lagos

BMC Medical Informatics Decis. Mak., 2021

Mathematical Model for Estimating Nutritional Status of the Population with Poor Data Quality in Developing Countries: The Case of Chile.

Denisse Ávalos, Cristóbal Cuadrado, Jocelyn Dunstan, Javier Moraga, Luis Rojo-González, Nelson Troncoso, Óscar C. Vásquez

Proceedings of the 10th International Conference on Operations Research and Enterprise Systems, 2021

2020

Predicting nationwide obesity from food sales using machine learning.

Jocelyn Dunstan, Marcela Aguirre, Magdalena Bastías, Claudia Nau, Thomas A. Glass, Felipe A. Tobar

Health Informatics J., 2020

On the Construction of Multilingual Corpora for Clinical Text Mining.

Fabián Villena, Urs Eisenmann, Petra Knaup, Jocelyn Dunstan, Matthias Ganzinger

Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

The Chilean Waiting List Corpus: a new resource for clinical Named Entity Recognition in Spanish.

Pablo Báez, Fabián Villena, Matías Rojas, Manuel Durán, Jocelyn Dunstan

Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020