AIMC Topic: International Classification of Diseases

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Large Language Models for Psychiatric Diagnosis Based on Multicenter Real-World Clinical Records: Comparative Study.

JMIR medical informatics
BACKGROUND: Psychiatric disorders are diagnostically challenging and often rely on subjective clinical judgment, particularly in resource-limited settings. Large language models (LLMs) have demonstrated potential in supporting psychiatric diagnosis; ...

Representativeness of a German AI-enabled data network for secondary epidemiological analysis based on electronic health records.

PloS one
INTRODUCTION: The ongoing digitalization of medicine, increased computing power and low-cost storage capacities enable the use of AI-based algorithms for epidemiological big data analysis of electronic patient records. The aim of this study was to ev...

Natural Language Processing and Coding for Detecting Bleeding Events in Discharge Summaries: Comparative Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Bleeding adverse drug events (ADEs), particularly among older inpatients receiving antithrombotic therapy, represent a major safety concern in hospitals. These events are often underdetected by conventional rule-based systems relying on s...

Leveraging BERT for embedding ICD codes from large scale cardiovascular EMR data to understand patient diagnostic patterns.

BMC medical informatics and decision making
The integration of electronic medical records (EMRs) with artificial intelligence (AI) is enhancing medical research, particularly in real-world evidence (RWE) studies. Extracting insights from coded medical data, such as ICD-10 codes, is essential f...

Performance of Natural Language Processing versus International Classification of Diseases Codes in Building Registries for Patients With Fall Injury: Retrospective Analysis.

JMIR medical informatics
BACKGROUND: Standardized registries, such as the International Classification of Diseases (ICD) codes, are commonly built using administrative codes assigned to patient encounters. However, patients with fall injury are often coded using subsequent i...

Development and Validation of a Rule-Based Natural Language Processing Algorithm to Identify Falls in Inpatient Records of Older Adults: Retrospective Analysis.

JMIR aging
BACKGROUND: In order to address fall underestimation by the International Classification of Diseases (ICD) in clinical settings, information from clinical notes could be incorporated via natural language processing (NLP) as a possible solution. Howev...

Artificial Intelligence to Improve Clinical Coding Practice in Scandinavia: Crossover Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Clinical coding is critical for hospital reimbursement, quality assessment, and health care planning. In Scandinavia, however, coding is often done by junior doctors or medical secretaries, leading to high rates of coding errors. Artifici...

Documentation, Coding, and Billing for Neurologic Services and Procedures.

Seminars in neurology
Documentation, coding, and billing (claims submission) are foundational to neurologic practice in the United States, enabling accurate reimbursement, effective communication, and data-driven advancements in patient care, research, and education. Neur...

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study.

JMIR medical informatics
BACKGROUND: Congestive heart failure (CHF) is a common cause of hospital admissions. Medical records contain valuable information about CHF, but manual chart review is time-consuming. Claims databases (using International Classification of Diseases [...

How to leverage large language models for automatic ICD coding.

Computers in biology and medicine
ICD coding, which involves assigning appropriate ICD codes to clinical notes, is essential for healthcare tasks such as health expense claims, insurance claims, and disease research. Manual ICD coding is time-consuming and prone to errors, increasing...