AIMC Topic: International Classification of Diseases
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Using supervised machine learning and ICD10 to identify non-accidental trauma in pediatric trauma patients in the Maryland Health Services Cost Review Commission dataset.
Child abuse & neglect
Jan 11, 2025
BACKGROUND: Identifying non-accidental trauma (NAT) in pediatric trauma patients is challenging. We developed a machine learning model that uses demographic characteristics and ICD10 codes to detect the first diagnosis of NAT.
External validation of an artificial intelligence model using clinical variables, including ICD-10 codes, for predicting in-hospital mortality among trauma patients: a multicenter retrospective cohort study.
Scientific reports
Jan 7, 2025
Artificial intelligence (AI) is being increasingly applied in healthcare to improve patient care and clinical outcomes. We previously developed an AI model using ICD-10 (International Classification of Diseases, Tenth Revision) codes with other clini...
Autonomous International Classification of Diseases Coding Using Pretrained Language Models and Advanced Prompt Learning Techniques: Evaluation of an Automated Analysis System Using Medical Text.
JMIR medical informatics
Jan 6, 2025
BACKGROUND: Machine learning models can reduce the burden on doctors by converting medical records into International Classification of Diseases (ICD) codes in real time, thereby enhancing the efficiency of diagnosis and treatment. However, it faces ...
A Machine Learning Approach for Predicting In-Hospital Cardiac Arrest Using Single-Day Vital Signs, Laboratory Test Results, and International Classification of Disease-10 Block for Diagnosis.
Annals of laboratory medicine
Dec 13, 2024
BACKGROUND: Predicting in-hospital cardiac arrest (IHCA) is crucial for potentially reducing mortality and improving patient outcomes. However, most models, which rely solely on vital signs, may not comprehensively capture the patients' risk profiles...
LCDL: Classification of ICD codes based on disease label co-occurrence dependency and LongFormer with medical knowledge.
Artificial intelligence in medicine
Dec 7, 2024
Medical coding involves assigning codes to clinical free-text documents, specifically medical records that average over 3,000 markers, in order to track patient diagnoses and treatments. This is typically accomplished through manual assignments by he...
Extracting International Classification of Diseases Codes from Clinical Documentation Using Large Language Models.
Applied clinical informatics
Nov 28, 2024
BACKGROUND: Large language models (LLMs) have shown promise in various professional fields, including medicine and law. However, their performance in highly specialized tasks, such as extracting ICD-10-CM codes from patient notes, remains underexplo...
Comparison of deep learning approaches to estimate injury severity from the International Classification of Diseases codes.
Traffic injury prevention
Nov 1, 2024
OBJECTIVE: The injury severity classification based on the Abbreviated Injury Scale (AIS) provides information that allows for standardized comparisons for injury research. However, the majority of injury data is captured using the International Clas...
De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.
Clinical orthopaedics and related research
Oct 2, 2024
BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of soft tissue sarcoma in databases. The National VA Database provides a unique opportunity for soft tiss...
Evaluating a Natural Language Processing-Driven, AI-Assisted International Classification of Diseases, 10th Revision, Clinical Modification, Coding System for Diagnosis Related Groups in a Real Hospital Environment: Algorithm Development and Validation Study.
Journal of medical Internet research
Sep 20, 2024
BACKGROUND: International Classification of Diseases codes are widely used to describe diagnosis information, but manual coding relies heavily on human interpretation, which can be expensive, time consuming, and prone to errors. With the transition f...
Validation of anorexia nervosa and Bulimia nervosa diagnosis coding in Danish hospitals assisted by a natural language processing model.
Journal of psychiatric research
Sep 14, 2024
INTRODUCTION: The Danish Health Care Registers rely on the International Statistical Classification of Diseases and Related Health Problems (ICD)-classification and stand as a widely utilized resource for health epidemiological research. Eating disor...
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