AIMC Topic: International Classification of Diseases

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Mining peripheral arterial disease cases from narrative clinical notes using natural language processing.

Journal of vascular surgery
OBJECTIVE: Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative n...

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection.

PloS one
OBJECTIVES: Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-bas...

Large-scale identification of patients with cerebral aneurysms using natural language processing.

Neurology
OBJECTIVE: To use natural language processing (NLP) in conjunction with the electronic medical record (EMR) to accurately identify patients with cerebral aneurysms and their matched controls.

PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby...

A method for modeling co-occurrence propensity of clinical codes with application to ICD-10-PCS auto-coding.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely re...

COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on ...

Development and Validation of an Algorithm to Identify Nonalcoholic Fatty Liver Disease in the Electronic Medical Record.

Digestive diseases and sciences
BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Risk factors for NAFLD disease progression and liver-related outcomes remain incompletely understood due to the lack of computa...

[Comparison of ICD 10 and AIS with the Development of a Method for Automated Conversion].

Zeitschrift fur Orthopadie und Unfallchirurgie
BACKGROUND: Most of the current scores and outcome prediction calculations in traumatology are based on the Abbreviated Injury Scale (AIS). However, this is not routinely used for documentation and coding of injuries in many countries, including Germ...

A Framework for Identifying Genotypic Information from Clinical Records: Exploiting Integrated Ontology Structures to Transfer Annotations between ICD Codes and Gene Ontologies.

IEEE/ACM transactions on computational biology and bioinformatics
Although some methods are proposed for automatic ontology generation, none of them address the issue of integrating large-scale heterogeneous biomedical ontologies. We propose a novel approach for integrating various types of ontologies efficiently a...