Drug Safety Report Generator
DOI:
https://doi.org//10.32628/CSEIT21743Keywords:
Adverse Drug Events, Drugs, Extraction Text, Dependency Parser, Patient identification, Medical History, Natural Language Processing, Text Mining, ICSR (Individual Case Study Report)Abstract
This document provides an overview on identifying ICSR (Individual case safety reports) & Drug Safety Classification of Adverse Drug Events from free Text Electronic Patient Records and Information. As a remarkable rise is observed in the usage of digital health records the potential for extensive clinical data extraction has drawn much attention. We intend to separate the causes and effects of unfriendly drugs from the records. We have therefore promoted a machine learning-based framework for the planned signature test of hostile drugs or safe phrases in the event of a report. In addition, the framework also uses named substance recognition based on word references to identify drugs and diseases that are present at the same time. The framework evaluation of physical comments in the corpus and a context-related analysis of consumption, which was carried out on preselected drugs, showed convincing results.
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