System for Medical Concept Extraction and Linking
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Updated
Aug 12, 2024 - Python
System for Medical Concept Extraction and Linking
Flexible and powerful platform for biomedical information extraction from text
[ECCV 2024 Oral] ConceptExpress: Harnessing Diffusion Models for Single-image Unsupervised Concept Extraction
CoCo-Ex extracts meaningful concepts from natural language texts and maps them to conjunct concept nodes in ConceptNet, utilizing the maximum of relational information stored in the ConceptNet knowledge graph.
Tools for Formal Concept Analysis
Concept extraction from MIMIC3 notes
Explainability of Deep Learning Models
CME: Concept-based Model Extraction
Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
Simple spaCy-based concept extraction API, involving a dictionary of relevant concepts.
A toolkit to do concept expansion via search engine snippet
Combining Energy-Based Modeling and RL to solve the challenging Abstract Reasoning Corpus[1] tasks.
create concept map from textbook data
MEME: Generating RNN Model Explanations via Model Extraction
Software created within Accumulate project (www.accumulate.be) at CLiPS, University of Antwerp
The replication package of STRICT: Search Term Identification for Concept Location using Graph-Based Term Weighting
CoCo-Ex extracts meaningful concepts from natural language texts and maps them to conjunct concept nodes in ConceptNet, utilizing the maximum of relational information stored in the ConceptNet knowledge graph.
Severity-focused biomedical concept normalization in Python
Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.
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