AIMC Topic: International Classification of Diseases

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Detection of probable dementia cases in undiagnosed patients using structured and unstructured electronic health records.

BMC medical informatics and decision making
BACKGROUND: Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approaches are therefore necessary ...

An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Code assignment is of paramount importance in many levels in modern hospitals, from ensuring accurate billing process to creating a valid record of patient care history. However, the coding process is tedious and subjective,...

Interpretable deep learning to map diagnostic texts to ICD-10 codes.

International journal of medical informatics
BACKGROUND: Automatic extraction of morbid disease or conditions contained in Death Certificates is a critical process, useful for billing, epidemiological studies and comparison across countries. The fact that these clinical documents are written in...

A cross-lingual approach to automatic ICD-10 coding of death certificates by exploring machine translation.

Journal of biomedical informatics
Automatic ICD-10 coding is an unresolved challenge in terms of Machine Learning tasks. Despite hospitals generating an enormous amount of clinical documents, data is considerably sparse, associated with a very skewed and unbalanced code distribution,...

An open access medical knowledge base for community driven diagnostic decision support system development.

BMC medical informatics and decision making
INTRODUCTION: While early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will remain an important component ...

Neural transfer learning for assigning diagnosis codes to EMRs.

Artificial intelligence in medicine
OBJECTIVE: Electronic medical records (EMRs) are manually annotated by healthcare professionals and specialized medical coders with a standardized set of alphanumeric diagnosis and procedure codes, specifically from the International Classification o...

[An online dynamic knowledge base in multiple languages on general medicine and primary care].

The Pan African medical journal
INTRODUCTION: The International Classification of Primary Care, Second version (ICPC-2) aligned with the 10th Revision of the International Classification of Disease (ICD-10) is a standard for primary care epidemiology compendium. ICPC-2 has been als...

Use of natural language processing in electronic medical records to identify pregnant women with suicidal behavior: towards a solution to the complex classification problem.

European journal of epidemiology
We developed algorithms to identify pregnant women with suicidal behavior using information extracted from clinical notes by natural language processing (NLP) in electronic medical records. Using both codified data and NLP applied to unstructured cli...

Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluate the performance of a classifier, trained on structured EHR data, in identifying prostate cancer patients with metastatic disease. Using EHR data for...

Computer-Assisted Diagnostic Coding: Effectiveness of an NLP-based approach using SNOMED CT to ICD-10 mappings.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Computer-assisted (diagnostic) coding (CAC) aims to improve the operational productivity and accuracy of clinical coders. The level of accuracy, especially for a wide range of complex and less prevalent clinical cases, remains an open research proble...