Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies
MG Kersloot, FJP van Putten, A Abu-Hanna… - Journal of biomedical …, 2020 - Springer
Background Free-text descriptions in electronic health records (EHRs) can be of interest for
clinical research and care optimization. However, free text cannot be readily interpreted by a …
clinical research and care optimization. However, free text cannot be readily interpreted by a …
Automated ICD-9 coding via a deep learning approach
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 …
describe a patient's diagnosis. Accurate automated ICD-9 coding is important because …
An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes
Abstract Background and Objective Code assignment is of paramount importance in many
levels in modern hospitals, from ensuring accurate billing process to creating a valid record …
levels in modern hospitals, from ensuring accurate billing process to creating a valid record …
An empirical evaluation of supervised learning approaches in assigning diagnosis codes to electronic medical records
R Kavuluru, A Rios, Y Lu - Artificial intelligence in medicine, 2015 - Elsevier
Background Diagnosis codes are assigned to medical records in healthcare facilities by
trained coders by reviewing all physician authored documents associated with a patient's …
trained coders by reviewing all physician authored documents associated with a patient's …
Automatic ICD-9 coding via deep transfer learning
ICD-9 codes have been widely used to describe a patient's diagnosis. Accurate automatic
ICD-9 coding is important because manual coding is expensive, time-consuming. Inspired …
ICD-9 coding is important because manual coding is expensive, time-consuming. Inspired …
Explainable prediction of medical codes with knowledge graphs
F Teng, W Yang, L Chen, LF Huang… - Frontiers in bioengineering …, 2020 - frontiersin.org
International Classification of Diseases (ICD) is an authoritative health care classification
system of different diseases. It is widely used for disease and health records, assisted …
system of different diseases. It is widely used for disease and health records, assisted …
Diagnosis code assignment using sparsity-based disease correlation embedding
With the latest developments in database technologies, it becomes easier to store the
medical records of hospital patients from their first day of admission than was previously …
medical records of hospital patients from their first day of admission than was previously …
[PDF][PDF] Machine Learning Techniques for Electronic Health Records: Review of a Decade of Research
Advancement in Machine Learning (ML) has opened new gateways for transforming the
healthcare sector. This paper explores the integration of ML techniques within the …
healthcare sector. This paper explores the integration of ML techniques within the …
Construction of a semi-automatic ICD-10 coding system
L Zhou, C Cheng, D Ou, H Huang - BMC medical informatics and decision …, 2020 - Springer
Abstract Background The International Classification of Diseases, 10th Revision (ICD-10)
has been widely used to describe the diagnosis information of patients. Automatic ICD-10 …
has been widely used to describe the diagnosis information of patients. Automatic ICD-10 …
Multi-channel, convolutional attention based neural model for automated diagnostic coding of unstructured patient discharge summaries
Effective coding of patient records in hospitals is an essential requirement for epidemiology,
billing, and managing insurance claims. The prevalent practice of manual coding, carried …
billing, and managing insurance claims. The prevalent practice of manual coding, carried …