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International Classification of Diseases

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Overview of ICD-11 architecture and structure.

BMC medical informatics and decision making
BACKGROUND: The International Classification of Diseases (ICD) has progressed from a short list of causes of death to become the predominant classification of human diseases, syndromes, and conditions around the world. The World Health Organization h...

Hierarchical label-wise attention transformer model for explainable ICD coding.

Journal of biomedical informatics
International Classification of Diseases (ICD) coding plays an important role in systematically classifying morbidity and mortality data. In this study, we propose a hierarchical label-wise attention Transformer model (HiLAT) for the explainable pred...

Use of neural network based on international classification ICD-10 in patients with head and neck injuries in Lublin Province, Poland, between 2006-2018, as a predictive value of the outcomes of injury sustained.

Annals of agricultural and environmental medicine : AAEM
INTRODUCTION AND OBJECTIVE: Head and neck injuries are a heterogeneous group in terms of both clinical course and prognosis. For years, there have been attempts to create an ideal tool to predict the outcomes and severity of injuries. The aim of this...

Using natural language processing to identify child maltreatment in health systems.

Child abuse & neglect
BACKGROUND: Rates of child maltreatment (CM) obtained from electronic health records are much lower than national child welfare prevalence rates indicate. There is a need to understand how CM is documented to improve reporting and surveillance.

Defining the distance between diseases using SNOMED CT embeddings.

Journal of biomedical informatics
Characterizing disease relationships is essential to biomedical research to understand disease etiology and improve clinical decision-making. Measurements of distance between disease pairs enable valuable research tasks, such as subgrouping patients ...

Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment.

Studies in health technology and informatics
Clinical information systems have become large repositories for semi-structured and partly annotated electronic health record data, which have reached a critical mass that makes them interesting for supervised data-driven neural network approaches. W...

Ontology-driven and weakly supervised rare disease identification from clinical notes.

BMC medical informatics and decision making
BACKGROUND: Computational text phenotyping is the practice of identifying patients with certain disorders and traits from clinical notes. Rare diseases are challenging to be identified due to few cases available for machine learning and the need for ...

Supervised Text Classification System Detects Fontan Patients in Electronic Records With Higher Accuracy Than Codes.

Journal of the American Heart Association
Background The Fontan operation is associated with significant morbidity and premature mortality. Fontan cases cannot always be identified by () codes, making it challenging to create large Fontan patient cohorts. We sought to develop natural langua...

Multigranularity Label Prediction Model for Automatic International Classification of Diseases Coding in Clinical Text.

Journal of computational biology : a journal of computational molecular cell biology
International Classification of Diseases (ICD) serves as the foundation for generating comparable global disease statistics across regions and over time. The process of ICD coding involves assigning codes to diseases based on clinical notes, which ca...

Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention.

IEEE transactions on bio-medical engineering
OBJECTIVE: Heart failure, respiratory failure and kidney failure are three severe organ failures (OF) that have high mortalities and are most prevalent in intensive care units. The objective of this work is to offer insights into OF clustering from t...