AIMC Topic: International Classification of Diseases

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Automatic Medical Code Assignment via Deep Learning Approach for Intelligent Healthcare.

IEEE journal of biomedical and health informatics May 25, 2020
With the development of healthcare 4.0, there has been an explosion in the amount of data such as image, medical text, physiological signals, lab tests, etc. Among them, medical records provide a complete picture of the associated clinical events. Ho...
Electronic Health Records Deep Learning International Classification of Diseases Humans Artificial Intelligence Delivery of Health Care
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Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.

Diabetes care May 15, 2020
OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of fu...
Humans Clinical Decision Rules Information Storage and Retrieval International Classification of Diseases Community Health Planning Male Middle Aged Severity of Illness Index Aged Diabetes Mellitus, Type 2 Aged, 80 and over United States Young Adult Predictive Value of Tests Adult Natural Language Processing Hypoglycemia Algorithms Electronic Health Records Female
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A study of entity-linking methods for normalizing Chinese diagnosis and procedure terms to ICD codes.

Journal of biomedical informatics Apr 13, 2020
OBJECTIVE: This study aims to develop and evaluate effective methods that can normalize diagnosis and procedure terms written by physicians to standard concepts in International Classification of Diseases(ICD) in Chinese, with the goal to facilitate ...
Neural Networks, Computer China Support Vector Machine International Classification of Diseases Clinical Coding
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Machine learning application for incident prostate adenocarcinomas automatic registration in a French regional cancer registry.

International journal of medical informatics Apr 9, 2020
UNLABELLED: Cancer registries are collections of curated data about malignant tumor diseases. The amount of data processed by cancer registries increases every year, making manual registration more and more tedious.
Humans Machine Learning Algorithms Registries Data Mining Male France International Classification of Diseases Incidence Adenocarcinoma Prostatic Neoplasms
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Automated ICD coding via unsupervised knowledge integration (UNITE).

International journal of medical informatics Apr 4, 2020
OBJECTIVE: Accurate coding is critical for medical billing and electronic medical record (EMR)-based research. Recent research has been focused on developing supervised methods to automatically assign International Classification of Diseases (ICD) co...
Automation International Classification of Diseases Disease Humans Neural Networks, Computer Machine Learning Algorithms Electronic Health Records
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Automated screening of natural language in electronic health records for the diagnosis septic shock is feasible and outperforms an approach based on explicit administrative codes.

Journal of critical care Jan 9, 2020
PURPOSE: Identification of patients for epidemiologic research through administrative coding has important limitations. We investigated the feasibility of a search based on natural language processing (NLP) on the text sections of electronic health r...
False Positive Reactions International Classification of Diseases Predictive Value of Tests Natural Language Processing Epidemiologic Studies Pattern Recognition, Automated Middle Aged Incidence Shock, Septic Prospective Studies Intensive Care Units Electronic Health Records Female Hospitalization Young Adult Adult Sensitivity and Specificity Humans Software Databases, Factual
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Rule-based and machine learning algorithms identify patients with systemic sclerosis accurately in the electronic health record.

Arthritis research & therapy Dec 30, 2019
BACKGROUND: Systemic sclerosis (SSc) is a rare disease with studies limited by small sample sizes. Electronic health records (EHRs) represent a powerful tool to study patients with rare diseases such as SSc, but validated methods are needed. We devel...
International Classification of Diseases Scleroderma, Systemic Sensitivity and Specificity Male Middle Aged Humans Machine Learning Reproducibility of Results Aged Aged, 80 and over Adult Algorithms Databases, Factual Electronic Health Records Female
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Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity.

Computer methods and programs in biomedicine Dec 10, 2019
BACKGROUND AND OBJECTIVE: This work deals with clinical text mining, a field of Natural Language Processing applied to biomedical informatics. The aim is to classify Electronic Health Records with respect to the International Classification of Diseas...
Software Algorithms Electronic Health Records Deep Learning Natural Language Processing Data Mining Medical Informatics Humans Neural Networks, Computer Computer Graphics Pattern Recognition, Automated International Classification of Diseases Spain
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Mining multi-site clinical data to develop machine learning MRI biomarkers: application to neonatal hypoxic ischemic encephalopathy.

Journal of translational medicine Nov 21, 2019
BACKGROUND: Secondary and retrospective use of hospital-hosted clinical data provides a time- and cost-efficient alternative to prospective clinical trials for biomarker development. This study aims to create a retrospective clinical dataset of Magne...
International Classification of Diseases Hypoxia-Ischemia, Brain Magnetic Resonance Imaging Probability Clinical Trials as Topic Humans Machine Learning Algorithms Biomarkers Infant, Newborn Treatment Outcome
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Deep learning predicts extreme preterm birth from electronic health records.

Journal of biomedical informatics Oct 31, 2019
OBJECTIVE: Models for predicting preterm birth generally have focused on very preterm (28-32 weeks) and moderate to late preterm (32-37 weeks) settings. However, extreme preterm birth (EPB), before the 28th week of gestational age, accounts for the m...
International Classification of Diseases Infant, Newborn Humans Infant, Extremely Premature Algorithms Deep Learning Electronic Health Records Datasets as Topic
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