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acl2020-transition-discontinuous-ner

ade-drug-relation-extraction-from-clinical-notes

ade-relation-extraction

A research project on medical NLP. The objective is to extract ADE and related indications from clinical documents.

adverse-drug-effect-detection

This repo demonstrates how to train an NLP model that can detect adverse drug effects (ADEs) in phrases.

ahocorasick_rs

Check for multiple patterns in a single string at the same time: a fast Aho-Corasick algorithm for Python

anchoring_clinicalbert_ner

An anchoring approach to Medical Information Extraction using Clinical BERT Embeddings

bert-entity-extraction

bert-relation-extraction

PyTorch implementation for "Matching the Blanks: Distributional Similarity for Relation Learning" paper

bert_relation_extraction

bidirectional-lstm-crf-for-clinical-concept-extraction

Bidirectional LSTM-CRF for Clinical Concept Extraction using i2b2-2010 data

bio-ner

Biomedical Named Entity Recognition and Normalization of Diseases, Chemicals and Genenetic entity classes through the use of state-of-the-art models.

bioflair

BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling Tasks

biorelation-extraction-bert-sdp-triplets

chat-platform-nestjs

chat-platform-react

clinical-entity-recognition

Tensorflow implementation of CER on i2b2 dataset.

clinicalnlp-ade

Clinical NLP concept extraction of ADEs in the 2018 n2c2 Adverse Drug Events and Medication Extraction (Track 2). Includes data preprocessing, model training/evaluation scripts.

clinicaltransformerrelationextraction

A project for developing transformer-based models for clinical relation extraction

deep-learning-with-tensorflow-2-and-keras

Deep Learning with TensorFlow 2 and Keras, published by Packt

deeplearning-ai-examples

ehr-relation-extraction

NER and Relation Extraction from Electronic Health Records (EHR).

entity-recognition-datasets

A collection of corpora for named entity recognition (NER) and entity recognition tasks. These annotated datasets cover a variety of languages, domains and entity types.

fda-textmining

This project demonstrates a combination of rule-based and machine-learning-based Name Entity Extractors for Textual data

jerex

PyTorch code for JEREX: Joint Entity-Level Relation Extractor

keras-tutorial-odsc2020

Notebooks for Keras Tutorial presented at ODSC West 2020

klue-re-workspace

lectures

Oxford Deep NLP 2017 course

llama-adapter

Fine-tuning LLaMA to follow Instructions within 1 Hour and 1.2M Parameters

machine_learning_examples

A collection of machine learning examples and tutorials.

mastering-transformers

Mastering Transformers, published by Packt