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 …

Interpretable predictions of clinical outcomes with an attention-based recurrent neural network

Y Sha, MD Wang - Proceedings of the 8th ACM International Conference …, 2017 - dl.acm.org
The increasing accumulation of healthcare data provides researchers with ample
opportunities to build machine learning approaches for clinical decision support and to …

[HTML][HTML] Predicting mental conditions based on “history of present illness” in psychiatric notes with deep neural networks

T Tran, R Kavuluru - Journal of biomedical informatics, 2017 - Elsevier
Background: Applications of natural language processing to mental health notes are not
common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 …

Neural transfer learning for assigning diagnosis codes to EMRs

A Rios, R Kavuluru - Artificial intelligence in medicine, 2019 - Elsevier
Abstract Objective Electronic medical records (EMRs) are manually annotated by healthcare
professionals and specialized medical coders with a standardized set of alphanumeric …

A hierarchical method to automatically encode Chinese diagnoses through semantic similarity estimation

W Ning, M Yu, R Zhang - BMC medical informatics and decision making, 2016 - Springer
Background The accumulation of medical documents in China has rapidly increased in the
past years. We focus on develo** a method that automatically performs ICD-10 code …

Natural language processing and machine learning to identify people who inject drugs in electronic health records

D Goodman-Meza, A Tang, B Aryanfar… - Open forum …, 2022 - academic.oup.com
Background Improving the identification of people who inject drugs (PWID) in electronic
medical records can improve clinical decision making, risk assessment and mitigation, and …

[HTML][HTML] EMR coding with semi–parametric multi–head matching networks

A Rios, R Kavuluru - Proceedings of the conference. Association …, 2018 - ncbi.nlm.nih.gov
Coding EMRs with diagnosis and procedure codes is an indispensable task for billing,
secondary data analyses, and monitoring health trends. Both speed and accuracy of coding …

Multi-label classification methods for improving comorbidities identification

A Wosiak, K Glinka, D Zakrzewska - Computers in biology and medicine, 2018 - Elsevier
The medical diagnostic process may be supported by computational classification
techniques. In many cases, patients are affected by multiple illnesses, and more than one …

Improving children diagnostics by efficient multi-label classification method

K Glinka, A Wosiak, D Zakrzewska - … 2016 Kamień Śląski, Poland, June 20 …, 2016 - Springer
Using intelligent computational methods may support children diagnostics process. As in
many cases patients are affected by multiple illnesses, multi-perspective view on patient …

Analyzing Diagnostic Discrepancies in Emergency Department Using the TriNetX Big Data

X Huo, J Finkelstein - 2023 IEEE International Conference on …, 2023 - ieeexplore.ieee.org
The diagnostic discrepancies between emergency department diagnosis and hospital
discharge diagnosis could affect patient outcomes. The aim of this study was to analyze the …