LITERATURE REVIEW INFORMATION EXTRACTION PADA TEKS BIOMEDICAL DENGAN PENDEKATAN MACHINE LEARNING DAN NAMED ENTITY RECOGNITION

Rizki Ariyani

Jurnal Ilmiah Teknik (JUIT)
Vol. 2 No. 1 (2023): Januari : Jurnal Ilmiah Teknik

Extraction of information or information extraction is a field of science for natural language processing, by converting unstructured into information in a structured form. Information that is useful and requires data that can be used as a reference in making decisions. Machine Learning Algorithms have been used to build basic classification models to identify pediatrics in biomedical texts and have been developed to provide more accurate information. Named Entity Recognition (NER) is useful to help identify and identify a word. The biomedical field has a lot of literature so that NER is highly demanded in the biomedical domain. Biomedical texts are not homogeneous. Medical notes or records written differently from scientific articles, sequence annotations, or other recent public health. Various methods in biomedicine can be recognized, the meaning of which has been developed using machine learning. This study discusses previous research on NER in the biomedical sector.