AIMC Topic: Clinical Coding

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Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.

Journal of biomedical informatics
We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep n...

Assigning clinical codes with data-driven concept representation on Dutch clinical free text.

Journal of biomedical informatics
Clinical codes are used for public reporting purposes, are fundamental to determining public financing for hospitals, and form the basis for reimbursement claims to insurance providers. They are assigned to a patient stay to reflect the diagnosis and...

Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Phenotyping algorithms applied to electronic health record (EHR) data enable investigators to identify large cohorts for clinical and genomic research. Algorithm development is often iterative, depends on fallible investigator intuition, a...

A method for modeling co-occurrence propensity of clinical codes with application to ICD-10-PCS auto-coding.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely re...

Assessing the Utility of Automatic Cancer Registry Notifications Data Extraction from Free-Text Pathology Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cancer Registries record cancer data by reading and interpreting pathology cancer specimen reports. For some Registries this can be a manual process, which is labour and time intensive and subject to errors. A system for automatic extraction of cance...

Using ontologies to improve semantic interoperability in health data.

Journal of innovation in health informatics
The present-day health data ecosystem comprises a wide array of complex heterogeneous data sources. A wide range of clinical, health care, social and other clinically relevant information are stored in these data sources. These data exist either as s...

Retrieval-Augmented Generation for ICD-10 Coding in German Clinical Texts - A Technical Case Report.

Studies in health technology and informatics
INTRODUCTION: Manual ICD-10 coding of German clinical texts is time-consuming and error-prone. This project aims to develop a semi-automated pipeline for efficient coding of unstructured medical documentation.

An Open-architecture AI Model for CPT Coding in Breast Surgery: Development, Validation, and Prospective Testing.

Annals of surgery
OBJECTIVE: To develop, validate, and prospectively test an open-architecture, transformer-based artificial Intelligence (AI) model to extract procedure codes from free-text breast surgery operative notes.

ICD code mapping model based on clinical text tree structure.

Artificial intelligence in medicine
With the rapid development and progress of big data and artificial intelligence technology, the ICD coding problem of electronic medical records has been effectively solved. The deep learning method, which replaces the manual coding method, has impro...

Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...