INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Admittance to emergency clinic information is usually a difficult, exorbitant and tedious cycle requiring broad cooperation with network overseers. This prompts potential deferrals in obtaining bits of knowledge from information, like conclusion or other clinical results. Medical care managers, clinical professionals, specialists and patients could benefit from a framework that uses a medical system which could separate significant data from medical services information in constant. In this project, we present an inquiry addressing framework which works using machine learning that permits wellbeing experts to interface with a enormous scope information base by posing inquiries in normal language. This framework is based upon the NLP model, which make an interpretation of a client’s solicitation into a SQL question, which is then passed to the information server to recover pertinent information. We additionally propose a profound bilinear comparability model to work on the created SQL inquiries by better matching terms in the client’s question with the information base mapping and substance.
Keywords:
NLP model, SQL question, SQL inquiries, Machine Learning, Medical system.
Cite Article:
"Disease Prediction Using Lab Reports", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1711 - 1714, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304270.pdf
Downloads:
000337067
Publication Details:
Published Paper ID: IJSDR2304270
Registration ID:205620
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1711 - 1714
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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