Journal of the American College of Surgeons
Sep 16, 2025
BACKGROUND: Because of technical limitations inherent to logistic regression, NSQIP benchmarking has historically risk adjusted for procedure using only 1 principal CPT code among other predictors. This has the potential to create bias (favorable or ...
To assess strategies for enhancing the generalizability of healthcare artificial intelligence models, we analyzed the impact of preprocessing approaches applied to medical free text, compared single- versus multiple-institution data models, and evalu...
Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Apr 23, 2025
BACKGROUND: Manual CPT coding from operative notes is a time-intensive process that adds to the administrative burden in healthcare. Large Language Models (LLMs) offer a promising solution, but their accuracy in assigning CPT codes based on full oper...
Proper codification of medical diagnoses and procedures is essential for optimized health care management, quality improvement, research, and reimbursement tasks within large healthcare systems. Assignment of diagnostic or procedure codes is a tediou...
BMC medical informatics and decision making
Nov 23, 2021
BACKGROUND: In surgical department, CPT code assignment has been a complicated manual human effort, that entails significant related knowledge and experience. While there are several studies using CPTs to make predictions in surgical services, litera...
Classification systems such as ICD-10 for diagnoses or the Swiss Operation Classification System (CHOP) for procedure classification in the clinical treatment are essential for clinical management and information exchange. Traditionally, classificati...
BMC medical informatics and decision making
Dec 11, 2015
BACKGROUND: Interoperable phenotyping algorithms, needed to identify patient cohorts meeting eligibility criteria for observational studies or clinical trials, require medical data in a consistent structured, coded format. Data heterogeneity limits s...
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.
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