AIMC Topic: International Classification of Diseases
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Validation of GPT-4 for clinical event classification: A comparative analysis with ICD codes and human reviewers.
Journal of gastroenterology and hepatology
Apr 16, 2024
BACKGROUND AND AIM: Effective clinical event classification is essential for clinical research and quality improvement. The validation of artificial intelligence (AI) models like Generative Pre-trained Transformer 4 (GPT-4) for this task and comparis...
Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).
Health services research
Mar 30, 2024
OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.
Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.
American journal of ophthalmology
Feb 1, 2024
PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may...
Automatic ICD-10-CM coding via Lambda-Scaled attention based deep learning model.
Methods (San Diego, Calif.)
Dec 21, 2023
The International Classification of Diseases (ICD) serves as a global healthcare administration standard, with one of its editions being ICD-10-CM, an enhanced diagnostic classification system featuring numerous new codes for specific anatomic sites,...
TraumaICD Bidirectional Encoder Representation From Transformers: A Natural Language Processing Algorithm to Extract Injury International Classification of Diseases, 10th Edition Diagnosis Code From Free Text.
Annals of surgery
Sep 27, 2023
OBJECTIVE: To develop and validate TraumaICDBERT, a natural language processing algorithm to predict injury International Classification of Diseases, 10th edition (ICD-10) diagnosis codes from trauma tertiary survey notes.
Multigranularity Label Prediction Model for Automatic International Classification of Diseases Coding in Clinical Text.
Journal of computational biology : a journal of computational molecular cell biology
Jul 31, 2023
International Classification of Diseases (ICD) serves as the foundation for generating comparable global disease statistics across regions and over time. The process of ICD coding involves assigning codes to diseases based on clinical notes, which ca...
Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention.
IEEE transactions on bio-medical engineering
Jul 18, 2023
OBJECTIVE: Heart failure, respiratory failure and kidney failure are three severe organ failures (OF) that have high mortalities and are most prevalent in intensive care units. The objective of this work is to offer insights into OF clustering from t...
Supervised Text Classification System Detects Fontan Patients in Electronic Records With Higher Accuracy Than Codes.
Journal of the American Heart Association
Jun 22, 2023
Background The Fontan operation is associated with significant morbidity and premature mortality. Fontan cases cannot always be identified by () codes, making it challenging to create large Fontan patient cohorts. We sought to develop natural langua...
Ontology-driven and weakly supervised rare disease identification from clinical notes.
BMC medical informatics and decision making
May 5, 2023
BACKGROUND: Computational text phenotyping is the practice of identifying patients with certain disorders and traits from clinical notes. Rare diseases are challenging to be identified due to few cases available for machine learning and the need for ...
Using natural language processing to identify child maltreatment in health systems.
Child abuse & neglect
Feb 8, 2023
BACKGROUND: Rates of child maltreatment (CM) obtained from electronic health records are much lower than national child welfare prevalence rates indicate. There is a need to understand how CM is documented to improve reporting and surveillance.
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