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International Classification of Diseases

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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...

Scalable Electronic Phenotyping For Studying Patient Comorbidities.

AMIA ... Annual Symposium proceedings. AMIA Symposium
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
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
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...

Open Globe Injury Patient Identification in Warfare Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The aim of this study is to utilize the Defense and Veterans Eye Injury and Vision Registry clinical data derived from DoD and VA medical systems which include documentation of care while in combat, and develop methods for comprehensive and reliable ...

Automated ICD-9 Coding via A Deep Learning Approach.

IEEE/ACM transactions on computational biology and bioinformatics
ICD-9 (the Ninth Revision of International Classification of Diseases) is widely used to describe a patient's diagnosis. Accurate automated ICD-9 coding is important because manual coding is expensive, time-consuming, and inefficient. Inspired by the...

Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.

Journal of biomedical informatics
We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep n...

Machine Learning Approaches on Diagnostic Term Encoding With the ICD for Clinical Documentation.

IEEE journal of biomedical and health informatics
This work focuses on data mining applied to the clinical documentation domain. Diagnostic terms (DTs) are used as keywords to retrieve valuable information from electronic health records. Indeed, they are encoded manually by experts following the Int...

Word2Vec inversion and traditional text classifiers for phenotyping lupus.

BMC medical informatics and decision making
BACKGROUND: Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text cl...