Cardiology record multi-label classification using latent Dirichlet allocation
J Pérez, A Pérez, A Casillas, K Gojenola - Computer methods and …, 2018 - Elsevier
Abstract Background and Objectives Electronic health records (EHRs) convey vast and
valuable knowledge about dynamically changing clinical practices. Indeed, clinical …
valuable knowledge about dynamically changing clinical practices. Indeed, clinical …
Multi-label clinical document classification: Impact of label-density
Objective The goal of this work is the classification of Electronic Health Records using
Natural Language Techniques. Electronic Health Records (EHRs) convey valuable clinical …
Natural Language Techniques. Electronic Health Records (EHRs) convey valuable clinical …
Transformers for multi-label classification of medical text: an empirical comparison
Recent advancements in machine learning-based multi-label medical text classification
techniques have been used to help enhance healthcare and aid better patient care. This …
techniques have been used to help enhance healthcare and aid better patient care. This …
[HTML][HTML] Implementation of specialised attention mechanisms: ICD-10 classification of Gastrointestinal discharge summaries in English, Spanish and Swedish
A Blanco, S Remmer, A Perez, H Dalianis… - Journal of Biomedical …, 2022 - Elsevier
Multi-label classification according to the International Classification of Diseases (ICD) is an
Extreme Multi-label Classification task aiming to categorise health records according to a set …
Extreme Multi-label Classification task aiming to categorise health records according to a set …
Divide and conquer: An extreme multi-label classification approach for coding diseases and procedures in Spanish
Clinical coding is the task of transforming medical documents into structured codes following
a standard ontology. Since these terminologies are composed of hundreds of codes, this …
a standard ontology. Since these terminologies are composed of hundreds of codes, this …
Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity
A Blanco, O Perez-de-Vinaspre, A Pérez… - Computer methods and …, 2020 - Elsevier
Background and objective: This work deals with clinical text mining, a field of Natural
Language Processing applied to biomedical informatics. The aim is to classify Electronic …
Language Processing applied to biomedical informatics. The aim is to classify Electronic …
Extreme multi-label ICD classification: sensitivity to hospital service and time
A Blanco, A Perez, A Casillas - IEEE Access, 2020 - ieeexplore.ieee.org
This work deals with clinical text mining for automatic classification of Electronic Health
Records (EHRs) with respect to the International Classification of Diseases (ICD). ICD is the …
Records (EHRs) with respect to the International Classification of Diseases (ICD). ICD is the …
Explainable ICD multi-label classification of EHRs in Spanish with convolutional attention
Background This work deals with Natural Language Processing applied to Electronic Health
Records (EHRs). EHRs are coded following the International Classification of Diseases …
Records (EHRs). EHRs are coded following the International Classification of Diseases …
Exploiting ICD Hierarchy for Classification of EHRs in Spanish through multi-task Transformers
A Blanco, A Pérez, A Casillas - IEEE journal of biomedical and …, 2021 - ieeexplore.ieee.org
Electronic Health Records (EHRs) convey valuable information. Experts in clinical
documentation read the report, understand the prior work, procedures, tests carried out, and …
documentation read the report, understand the prior work, procedures, tests carried out, and …
Dkec: Domain knowledge enhanced multi-label classification for electronic health records
Multi-label text classification (MLTC) tasks in the medical domain often face long-tail label
distribution, where rare classes have fewer training samples than frequent classes. Although …
distribution, where rare classes have fewer training samples than frequent classes. Although …