AIMC Topic: Clinical Coding
Clear Filters Showing 21 to 30 of 71 articles
Artificial Intelligence for Unstructured Healthcare Data: Application to Coding of Patient Reporting of Adverse Drug Reactions.
Clinical pharmacology and therapeutics
May 8, 2021
Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its input will, however, only be optimized if systems can manage to deal with its tremendous flow of information, based primarily on unstructured text fields. The a...
Explainable automated coding of clinical notes using hierarchical label-wise attention networks and label embedding initialisation.
Journal of biomedical informatics
Mar 9, 2021
BACKGROUND: Diagnostic or procedural coding of clinical notes aims to derive a coded summary of disease-related information about patients. Such coding is usually done manually in hospitals but could potentially be automated to improve the efficiency...
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 ...
Machine learning and the future of Medicare fraud detection.
Journal of the American Academy of Dermatology
Mar 29, 2020
Medi-Care AI: Predicting medications from billing codes via robust recurrent neural networks.
Neural networks : the official journal of the International Neural Network Society
Jan 23, 2020
In this paper, we present an effective deep prediction framework based on robust recurrent neural networks (RNNs) to predict the likely therapeutic classes of medications a patient is taking, given a sequence of diagnostic billing codes in their reco...
Incorporating medical code descriptions for diagnosis prediction in healthcare.
BMC medical informatics and decision making
Dec 19, 2019
BACKGROUND: Diagnosis aims to predict the future health status of patients according to their historical electronic health records (EHR), which is an important yet challenging task in healthcare informatics. Existing diagnosis prediction approaches m...
Leveraging Semantics in WordNet to Facilitate the Computer-Assisted Coding of ICD-11.
IEEE journal of biomedical and health informatics
Oct 25, 2019
The International Classification of Diseases (ICD) not only serves as the bedrock for health statistics but also provides a holistic overview of every health aspect of life. This study aims to facilitate the computer-assisted coding of the 11th revis...
Use of Natural Language Processing to identify Obsessive Compulsive Symptoms in patients with schizophrenia, schizoaffective disorder or bipolar disorder.
Scientific reports
Oct 2, 2019
Obsessive and Compulsive Symptoms (OCS) or Obsessive Compulsive Disorder (OCD) in the context of schizophrenia or related disorders are of clinical importance as these are associated with a range of adverse outcomes. Natural Language Processing (NLP)...
A two-stage deep learning approach for extracting entities and relationships from medical texts.
Journal of biomedical informatics
Sep 20, 2019
This work presents a two-stage deep learning system for Named Entity Recognition (NER) and Relation Extraction (RE) from medical texts. These tasks are a crucial step to many natural language understanding applications in the biomedical domain. Autom...
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...
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