Development and evaluation of a model for effective translation of patient complaints in natural language to relevant medical terms by using following NLP techniques
DOI:
https://doi.org/10.52783/jns.v14.2254Keywords:
Patient Complaints, Medical Terminology, Marathi Language, Natural Language Processing (NLP), Healthcare, Medical Records, Symptom Translation, Machine LearningAbstract
It is critical for healthcare services to comprehend the complaints of patients spoken in their own language and convert them into medical terms. This paper aims to develop and evaluate a model to translate the patients' complaints in Marathi to proper medical terms. There are different ways to do it, each with its pros and cons. Examples of such techniques are direct translation based on word dictionaries, rule-based extraction, Ontology mapping as well as Ontology mapping with Named Entity Recognition (NER). The model will enable doctors and health care systems to better comprehend the problems of patients by intelligently using texts with natural language processing (NLP) and medical vocabularies. It will also assist in keeping correct medical records, facilitate improved medical decision making, and streamline healthcare systems.
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