Precision in Parsing: Evaluation of an Open-Source Named Entity Recognizer (NER) in Veterinary Oncology.

ABSTRACT: Integrating Artificial Intelligence (AI) through Natural Language Processing (NLP) can improve veterinary medical oncology clinical record analytics. Named Entity Recognition (NER), a critical component of NLP, can facilitate efficient data extraction and automated labelling for research and clinical decision-making. This study assesses the efficacy of the Bio-Epidemiology-NER (BioEN), an open-source NER developed using human epidemiological and medical data, on veterinary medical oncology records. The NER's performance was compared with manual annotations by a veterinary medical oncologist and a veterinary intern. Evaluation metrics included Jaccard similarity, intra-rater reliability, ROUGE scores, and standard NER performance metrics (precision, recall, F1-score). Results indicate poor

SUBMITTER: Pinard CJ 

PROVIDER: S-EPMC11830456 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature