Domaines médical et juridique [FR]

Les techniques de traitement du langage naturel nécessitent généralement d'adaptation lorsqu'elles sont utilisées dans des domaines spécifiques tels que les domaines médical et juridique.

Dans le domaine de la santé, nous avons commencé en 2010 à collaborer avec l'hôpital de Galdakao-Usansolo dans le but d'améliorer l'encodage de leurs dossiers de santé d'accord avec la Classification Internationale des Maladies (CIM). Par la suite, et toujours dans l'intérêt des patients, nous avons travaillé sur différents domaines : la détection des effets indésirables des médicaments, la reconnaissance des entités cliniques nommées (médicaments, troubles de santé, noms des parties du corps...) et dernièrement la traduction automatique des dossiers de santé électroniques (DSE). Nous avons principalement travaillé avec des DSE en espagnol, mais nous avons aussi utilisé des corpus médicaux en anglais, et ce qui est très important pour nous, nous avons fait des pas importants pour amener le basque aux services de santé. En ce sens, nous avons traduit automatiquement l'énorme lexique médical SNOMED-CT de l'anglais vers le basque, et nous avons obtenu nos premiers résultats en traduction automatique neuronale entre basque et espagnol.

En collaboration avec quelques hôpitaux du Système Sanitaire Basque (Osakidetza), nous avons travaillé dans les projets de recherche OSAKU, DETEAMI, EXTRECM et PROSAMED et nous avons obtenu un contrat d'Osakidetza pour la traduction automatique de la CIM-10 en Basque.

Dans le domaine juridique, nous avons été contractés par Minsait pour collaborer à Prótagoras, un projet interne qui vise à construire un système de compréhension du langage naturel pour l'espagnol. Nous nous sommes concentrés dans le domaine juridique, dans lequel le back-office génère une énorme quantité de documentation administrative qui doit être enregistrée et organisée très rapidement pour permettre une prise de décision efficace.

Dans le projet nous avons présenté une solution pour un cas réel d'extraction d'information des actes notariés, en remplissant l'objectif d'alléger le coût de l'effort manuel. Ainsi, sans utiliser de données étiquetées, nous avons développé des systèmes capables d'extraire les principaux attributs des propriétés décrites dans les documents (localité, nom de rue, numéro de propriété et prix, entre autres) ainsi que les informations sur les propriétaires (par exemple, noms et prénoms, type de propriété, etc.).

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Chercheur/se principal/e:

Arantza Casillas

Chercheurs:

Arantza Díaz de Ilarraza

Nerea Ezeiza

Iakes Goenaga

Koldo Gojenola

Oier Lopez de Lacalle

Maite Oronoz

Alicia Pérez

Olatz Perez de Viñaspre

domains_tabs

Demos

Clinical entity and relation extraction in Spanish

Insert a text from the clinical domain and the systems will detect the disorders, drugs, body parts and procedures in it as well as adverse drug reactions and relations between disorders

Contrats

Projects

Development Of Text-based Technology to support diagnosis, prevention and HEALTH institutions management
Development Of Text-based Technology to support diagnosis, prevention and HEALTH institutions management
(2020 - 2023)
PROSA-MED: Advanced semantic textual processing for the detection of diagnostic codes, procedures, concepts and their relationships in health records
(2016 - 2019)
DETEAMI: Automatic detection of adverse drug effects in medical reports using natural language processing technologies.
(2015 - 2018)

All HiTZ projects

Patents

System to detect Spanish medical entities in the medical domain

Publications

Alberto Blanco, Olatz Perez de Viñaspre, Alicia Pérez, Arantza Casillas

Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity (2020)

Computer Methods and Programs in Biomedicine, Volume 188, 105264

Rebecka Weegar, Alicia Pérez, Arantza Casillas, Maite Oronoz

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches (2020)

BMC Medical Informatics and Decision Making

Sara Santiso

Adverse Drug Reaction extraction on Electronic Health Records written in Spanish (2020)

Procesamiento del Lenguaje Natural http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6203

Sara Santiso, Alicia Pérez, Arantza Casillas, Maite Oronoz

Neural negated entity recognition in Spanish electronic health records (2020)

Journal of Biomedical Informatics (JBI) https://doi.org/10.1016/j.jbi.2020.103419

Alberto Blanco, Alicia Pérez, Arantza Casillas, Daniel Cobos

Extracting Cause of Death from Verbal Autopsy with Deep Learning interpretable methods (2020)

IEEE Journal of Biomedical and Health Informatics

Santana, S and Pérez, A and Casillas, A

HapLap at eHealth-KD Challenge 2020 (2020)

Proceedings of the Iberian Languages Evaluation Forum co-located with 36th Conference of the Spanish Society for Natural Language Processing, IberLEF@ SEPLN

Alberto Blanco, Alicia Pérez, Arantza Casillas

Extreme multi-label ICD classification: sensitivity to hospital service and time (2020)

IEEE Access, Volume 8, 183534-183545

Alberto Blanco, Alicia Pérez, Arantza Casillas

Automatic Classification of Medical Records with Multi-label Classifiers and Similarity Match Coders (2020)

CEUR Workshop Proceedings, Vol 2696 - Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum

Kepa Sarasola, Iñaki Alegria, Olatz Perez de Viñaspre

Language Technology for Language Communities: An Overview based on Basque Experience 2020 (2020)file2 (2020)

Symposiwm Academaidd Technolegau Iaith Cymru 2020 -11-04 // Wales Academic Symposium on Language Technologies 2020-11-04

Iker de la Iglesia, Mikel Martinez-Puente, Alexander Platas, Iria San Miguel, Aitziber Atutxa, Koldo Gojenola

MEDIA team at the CLEF-2020 MultilingualInformation Extraction Task (2020)

Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum Thessaloniki, Greece, September 22-25, 2020.

Sara Santiso, Alicia Pérez, Arantza Casillas

Smoothing dense spaces for improved relation extraction between drugs and adverse reactions (2019)

International Journal of Medical Informatics https://doi.org/10.1016/j.ijmedinf.2019.05.009

Aitziber Atutxa, Arantza Diaz de Ilarraza, koldo Gojenola,Maite Oronoz, Olatz Perez de Viñaspre

Interpretable Deep Learning to Map Diagnostic Texts to ICD10 Codes (2019)

International Journal of Medical Informatics https://doi.org/10.1016/j.ijmedinf.2019.05.015 Link to publication: https://authors.elsevier.com/c/1ZANI4xGJ~syOE

Arantza Casillas, Nerea Ezeiza, Iakes Goenaga, Alicia Pérez, Xabier Soto

Measuring the Effect of Different Types of Unsupervised Word Representations on Medical Named Entity Recognition (2019)

International Journal of Medical Informatics (https://doi.org/10.1016/j.ijmedinf.2019.05.022)

Alberto Blanco, Arantza Casillas, Alicia Pérez, Arantza Diaz de Ilarraza

Multi-label clinical document classification: Impact of label-density (2019)

Expert Systems with Applications, Volume 138, 112835

Olatz Perez-de-Viñaspre, Maite Oronoz, Natalia Elvira

KabiTermICD: Nested Term Based Translation of the ICD-10-CM into a Minor Language (2018)

Workshop "MultilingualBIO: Multilingual Biomedical Text Processing" of LREC 2018. Proceedings of the workshop. Miyazaki (Japan), 8th May 2018.

Jorge Pérez, Alicia Pérez, Arantza Casillas, Koldo Gojenola

Cardiology record multi-label classification using Latent Dirichlet Allocation (2018)

Computer Methods and Programs in Biomedicine https://doi.org/10.1016/j.cmpb.2018.07.002

Aitziber Atutxa, Arantza Casillas, Nerea Ezeiza, Iakes Goenaga, V. Fresno, Koldo Gojenola, R. Martinez, Maite Oronoz, Olatz Perez-de-Viñaspre

IxaMed at CLEF eHealth 2018 Task 1: ICD10 Coding with a Sequence-to-Sequence approach (2018)

CLEF 2018 Online Working Notes. CEUR-WS

Mikel Laburu, Alicia Pérez, Arantza Casillas, Iakes Goenaga, Maite Oronoz

Can I find information about rare diseases in some other language? (2018)

IEEE International Conference on Bioinformatics and Biomedicine. Artificial Intelligence techniques for Biomedicine and Healthcare. Madrid (December, 2018); ISBN: 978-1-5386-5487-3; Pgs: 2102-2108

All HiTZ publications

domains_tabs_full

Clinical entity and relation extraction in Spanish

Insert a text from the clinical domain and the systems will detect the disorders, drugs, body parts and procedures in it as well as adverse drug reactions and relations between disorders

Development Of Text-based Technology to support diagnosis, prevention and HEALTH institutions management
Development Of Text-based Technology to support diagnosis, prevention and HEALTH institutions management
(2020 - 2023)
PROSA-MED: Advanced semantic textual processing for the detection of diagnostic codes, procedures, concepts and their relationships in health records
(2016 - 2019)
DETEAMI: Automatic detection of adverse drug effects in medical reports using natural language processing technologies.
(2015 - 2018)

All HiTZ projects

System to detect Spanish medical entities in the medical domain

Alberto Blanco, Olatz Perez de Viñaspre, Alicia Pérez, Arantza Casillas

Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity (2020)

Computer Methods and Programs in Biomedicine, Volume 188, 105264

Rebecka Weegar, Alicia Pérez, Arantza Casillas, Maite Oronoz

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches (2020)

BMC Medical Informatics and Decision Making

Sara Santiso

Adverse Drug Reaction extraction on Electronic Health Records written in Spanish (2020)

Procesamiento del Lenguaje Natural http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6203

Sara Santiso, Alicia Pérez, Arantza Casillas, Maite Oronoz

Neural negated entity recognition in Spanish electronic health records (2020)

Journal of Biomedical Informatics (JBI) https://doi.org/10.1016/j.jbi.2020.103419

Alberto Blanco, Alicia Pérez, Arantza Casillas, Daniel Cobos

Extracting Cause of Death from Verbal Autopsy with Deep Learning interpretable methods (2020)

IEEE Journal of Biomedical and Health Informatics

Santana, S and Pérez, A and Casillas, A

HapLap at eHealth-KD Challenge 2020 (2020)

Proceedings of the Iberian Languages Evaluation Forum co-located with 36th Conference of the Spanish Society for Natural Language Processing, IberLEF@ SEPLN

Alberto Blanco, Alicia Pérez, Arantza Casillas

Extreme multi-label ICD classification: sensitivity to hospital service and time (2020)

IEEE Access, Volume 8, 183534-183545

Alberto Blanco, Alicia Pérez, Arantza Casillas

Automatic Classification of Medical Records with Multi-label Classifiers and Similarity Match Coders (2020)

CEUR Workshop Proceedings, Vol 2696 - Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum

Kepa Sarasola, Iñaki Alegria, Olatz Perez de Viñaspre

Language Technology for Language Communities: An Overview based on Basque Experience 2020 (2020)file2 (2020)

Symposiwm Academaidd Technolegau Iaith Cymru 2020 -11-04 // Wales Academic Symposium on Language Technologies 2020-11-04

Iker de la Iglesia, Mikel Martinez-Puente, Alexander Platas, Iria San Miguel, Aitziber Atutxa, Koldo Gojenola

MEDIA team at the CLEF-2020 MultilingualInformation Extraction Task (2020)

Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum Thessaloniki, Greece, September 22-25, 2020.

Sara Santiso, Alicia Pérez, Arantza Casillas

Smoothing dense spaces for improved relation extraction between drugs and adverse reactions (2019)

International Journal of Medical Informatics https://doi.org/10.1016/j.ijmedinf.2019.05.009

Aitziber Atutxa, Arantza Diaz de Ilarraza, koldo Gojenola,Maite Oronoz, Olatz Perez de Viñaspre

Interpretable Deep Learning to Map Diagnostic Texts to ICD10 Codes (2019)

International Journal of Medical Informatics https://doi.org/10.1016/j.ijmedinf.2019.05.015 Link to publication: https://authors.elsevier.com/c/1ZANI4xGJ~syOE

Arantza Casillas, Nerea Ezeiza, Iakes Goenaga, Alicia Pérez, Xabier Soto

Measuring the Effect of Different Types of Unsupervised Word Representations on Medical Named Entity Recognition (2019)

International Journal of Medical Informatics (https://doi.org/10.1016/j.ijmedinf.2019.05.022)

Alberto Blanco, Arantza Casillas, Alicia Pérez, Arantza Diaz de Ilarraza

Multi-label clinical document classification: Impact of label-density (2019)

Expert Systems with Applications, Volume 138, 112835

Olatz Perez-de-Viñaspre, Maite Oronoz, Natalia Elvira

KabiTermICD: Nested Term Based Translation of the ICD-10-CM into a Minor Language (2018)

Workshop "MultilingualBIO: Multilingual Biomedical Text Processing" of LREC 2018. Proceedings of the workshop. Miyazaki (Japan), 8th May 2018.

Jorge Pérez, Alicia Pérez, Arantza Casillas, Koldo Gojenola

Cardiology record multi-label classification using Latent Dirichlet Allocation (2018)

Computer Methods and Programs in Biomedicine https://doi.org/10.1016/j.cmpb.2018.07.002

Aitziber Atutxa, Arantza Casillas, Nerea Ezeiza, Iakes Goenaga, V. Fresno, Koldo Gojenola, R. Martinez, Maite Oronoz, Olatz Perez-de-Viñaspre

IxaMed at CLEF eHealth 2018 Task 1: ICD10 Coding with a Sequence-to-Sequence approach (2018)

CLEF 2018 Online Working Notes. CEUR-WS

Mikel Laburu, Alicia Pérez, Arantza Casillas, Iakes Goenaga, Maite Oronoz

Can I find information about rare diseases in some other language? (2018)

IEEE International Conference on Bioinformatics and Biomedicine. Artificial Intelligence techniques for Biomedicine and Healthcare. Madrid (December, 2018); ISBN: 978-1-5386-5487-3; Pgs: 2102-2108

All HiTZ publications

Languages

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Domaines médical et juridique [FR]

domains_tabs

System to detect Spanish medical entities in the medical domain

Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity (2020)

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches (2020)

Adverse Drug Reaction extraction on Electronic Health Records written in Spanish (2020)

Neural negated entity recognition in Spanish electronic health records (2020)

Extracting Cause of Death from Verbal Autopsy with Deep Learning interpretable methods (2020)

HapLap at eHealth-KD Challenge 2020 (2020)

Extreme multi-label ICD classification: sensitivity to hospital service and time (2020)

Automatic Classification of Medical Records with Multi-label Classifiers and Similarity Match Coders (2020)

Smoothing dense spaces for improved relation extraction between drugs and adverse reactions (2019)

Interpretable Deep Learning to Map Diagnostic Texts to ICD10 Codes (2019)

Multi-label clinical document classification: Impact of label-density (2019)

KabiTermICD: Nested Term Based Translation of the ICD-10-CM into a Minor Language (2018)

Cardiology record multi-label classification using Latent Dirichlet Allocation (2018)

domains_tabs_full

System to detect Spanish medical entities in the medical domain

Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity (2020)

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches (2020)

Adverse Drug Reaction extraction on Electronic Health Records written in Spanish (2020)

Neural negated entity recognition in Spanish electronic health records (2020)

Extracting Cause of Death from Verbal Autopsy with Deep Learning interpretable methods (2020)

HapLap at eHealth-KD Challenge 2020 (2020)

Extreme multi-label ICD classification: sensitivity to hospital service and time (2020)

Automatic Classification of Medical Records with Multi-label Classifiers and Similarity Match Coders (2020)

Smoothing dense spaces for improved relation extraction between drugs and adverse reactions (2019)

Interpretable Deep Learning to Map Diagnostic Texts to ICD10 Codes (2019)

Multi-label clinical document classification: Impact of label-density (2019)

KabiTermICD: Nested Term Based Translation of the ICD-10-CM into a Minor Language (2018)

Cardiology record multi-label classification using Latent Dirichlet Allocation (2018)

HiTZ est composé des groupes de recherche suivants: