AIMC Topic: Clinical Coding

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Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification.

BMC medical informatics and decision making Apr 4, 2019
BACKGROUND: Numbers and numerical concepts appear frequently in free text clinical notes from electronic health records. Knowledge of the frequent lexical variations of these numerical concepts, and their accurate identification, is important for man...
Clinical Coding Electronic Health Records Natural Language Processing Information Storage and Retrieval
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Clinical text classification with rule-based features and knowledge-guided convolutional neural networks.

BMC medical informatics and decision making Apr 4, 2019
BACKGROUND: Clinical text classification is an fundamental problem in medical natural language processing. Existing studies have cocnventionally focused on rules or knowledge sources-based feature engineering, but only a limited number of studies hav...
Humans Neural Networks, Computer Knowledge Bases Unified Medical Language System Clinical Coding Deep Learning Obesity Natural Language Processing
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EHR phenotyping via jointly embedding medical concepts and words into a unified vector space.

BMC medical informatics and decision making Dec 12, 2018
BACKGROUND: There has been an increasing interest in learning low-dimensional vector representations of medical concepts from Electronic Health Records (EHRs). Vector representations of medical concepts facilitate exploratory analysis and predictive ...
Phenotype Electronic Health Records Humans Natural Language Processing Machine Learning Terminology as Topic Vocabulary Clinical Coding
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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...
Unified Medical Language System Humans Clinical Coding Natural Language Processing Systematized Nomenclature of Medicine Electronic Health Records International Classification of Diseases Hospitals Australia
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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 ...
Humans Neural Networks, Computer Clinical Coding Electronic Health Records Pattern Recognition, Automated International Classification of Diseases
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Prediction task guided representation learning of medical codes in EHR.

Journal of biomedical informatics Jun 19, 2018
There have been rapidly growing applications using machine learning models for predictive analytics in Electronic Health Records (EHR) to improve the quality of hospital services and the efficiency of healthcare resource utilization. A fundamental an...
Algorithms Electronic Health Records Models, Statistical Humans Machine Learning Software Clinical Coding Regression Analysis Natural Language Processing Medical Informatics
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Identifying Falls Risk Screenings Not Documented with Administrative Codes Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Quality reporting that relies on coded administrative data alone may not completely and accurately depict providers' performance. To assess this concern with a test case, we developed and evaluated a natural language processing (NLP) approach to iden...
Mass Screening Natural Language Processing Information Storage and Retrieval Clinical Coding Humans Electronic Health Records Algorithms Risk Assessment Accidental Falls
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Predicting Changes in Pediatric Medical Complexity using Large Longitudinal Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Medically complex patients consume a disproportionate amount of care resources in hospitals but still often end up with sub-optimal clinical outcomes. Predicting dynamics of complexity in such patients can potentially help improve the quality of care...
Logistic Models Longitudinal Studies Area Under Curve Clinical Coding Humans Electronic Health Records Patient Acuity Neural Networks, Computer Child Health Services Child Data Mining ROC Curve Datasets as Topic
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An ontological approach to identifying cases of chronic kidney disease from routine primary care data: a cross-sectional study.

BMC nephrology Apr 10, 2018
BACKGROUND: Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management of patients, and is vital for surveillance and research purposes. Ontologies provide a systematic and transparent basis for cli...
Renal Insufficiency, Chronic Glomerular Filtration Rate Proteinuria Middle Aged United Kingdom Prevalence Humans Biological Ontologies Primary Health Care Renal Replacement Therapy Clinical Coding Cross-Sectional Studies Female Aged Male Aged, 80 and over Adult
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Automated ICD-9 Coding via A Deep Learning Approach.

IEEE/ACM transactions on computational biology and bioinformatics Mar 20, 2018
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...
Humans Neural Networks, Computer Algorithms Electronic Health Records Medical Informatics Reproducibility of Results International Classification of Diseases Deep Learning Clinical Coding Biomimetics
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