ExaNLP/sket
This repository contains the source code for the Semantic Knowledge Extractor Tool (SKET). SKET is an unsupervised hybrid knowledge extraction system that combines a rule-based expert system with pre-trained machine learning models to extract cancer-related information from pathology reports.
This tool helps oncologists and medical researchers quickly extract key cancer-related information from pathology reports. You input pathology reports, either as Excel spreadsheets or JSON files, and it outputs structured data like cancer types, patient demographics, and relationships between medical concepts. This is designed for medical professionals or researchers who need to analyze large volumes of unstructured clinical text.
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Use this if you need to automatically identify and organize specific cancer information from pathology reports for research or clinical analysis.
Not ideal if you're looking for a tool to analyze general medical text outside of cancer pathology or if your reports are not in Italian or English.
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Language
Python
License
MIT
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Last pushed
Apr 18, 2023
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