AIMC Topic: International Classification of Diseases
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A cross-lingual approach to automatic ICD-10 coding of death certificates by exploring machine translation.
Journal of biomedical informatics
May 8, 2019
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
Apr 27, 2019
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
Apr 12, 2019
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
Feb 5, 2019
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
Dec 10, 2018
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
Dec 5, 2018
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
Dec 5, 2018
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...
Scalable Electronic Phenotyping For Studying Patient Comorbidities.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Over 75 million Americans have multiple concurrent chronic conditions and medical decision making for these patients is mostly based on retrospective cohort studies. Current methods to generate cohorts of patients with comorbidities are neither scala...
Towards automated clinical coding.
International journal of medical informatics
Oct 2, 2018
BACKGROUND: Patients' encounters with healthcare services must undergo clinical coding. These codes are typically derived from free-text notes. Manual clinical coding is expensive, time-consuming and prone to error. Automated clinical coding systems ...
Benchmarking deep learning models on large healthcare datasets.
Journal of biomedical informatics
Jun 5, 2018
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist w...
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