Mednlp - Medical natural language parsing and utility library

Overview

Medical natural language parsing and utility library

PyPI Python 3.7 Python 3.8 Python 3.9 Build Status

A natural language medical domain parsing library. This library:

  • Provides an interface to the UTS (UMLS Terminology Services) RESTful service with data caching (NIH login needed).
  • Wraps the MedCAT library by parsing medical and clinical text into first class Python objects reflecting the structure of the natural language complete with UMLS entity linking with CUIs and other domain specific features.
  • Combines non-medical (such as POS and NER tags) and medical features (such as CUIs) in one API and resulting data structure and/or as a Pandas data frame.
  • Provides cui2vec as a word embedding model for either fast indexing and access or to use directly as features in a Zensols Deep NLP embedding layer model.
  • Provides access to cTAKES using as a dictionary like Stash abstraction.
  • Includes a command line program to access all of these features without having to write any code.

Documentation

See the full documentation. The API reference is also available.

Obtaining

The easiest way to install the command line program is via the pip installer:

pip3 install zensols.mednlp

Binaries are also available on pypi.

If the cui2vec functionality is used, the Zensols Deep NLP library is also needed, which is stalled with pip install zensols.deepnlp.

Attribution

This API utilizes the following frameworks:

  • MedCAT: used to extract information from Electronic Health Records (EHRs) and link it to biomedical ontologies like SNOMED-CT and UMLS.
  • cTAKES: a natural language processing system for extraction of information from electronic medical record clinical free-text.
  • cui2vec: a new set of (like word) embeddings for medical concepts learned using an extremely large collection of multimodal medical data.
  • Zensols Deep NLP library: a deep learning utility library for natural language processing that aids in feature engineering and embedding layers.
  • ctakes-parser: parses cTAKES output in to a Pandas data frame.

Citation

If you use this project in your research please use the following BibTeX entry:

@article{Landes_DiEugenio_Caragea_2021,
  title={DeepZensols: Deep Natural Language Processing Framework},
  url={http://arxiv.org/abs/2109.03383},
  note={arXiv: 2109.03383},
  journal={arXiv:2109.03383 [cs]},
  author={Landes, Paul and Di Eugenio, Barbara and Caragea, Cornelia},
  year={2021},
  month={Sep}
}

Community

Please star the project and let me know how and where you use this API. Contributions as pull requests, feedback and any input is welcome.

Changelog

An extensive changelog is available here.

License

MIT License

Copyright (c) 2021 - 2022 Paul Landes

Owner
Paul Landes
Paul Landes
Deep Learning for Natural Language Processing - Lectures 2021

This repository contains slides for the course "20-00-0947: Deep Learning for Natural Language Processing" (Technical University of Darmstadt, Summer term 2021).

0 Feb 21, 2022
An easy-to-use Python module that helps you to extract the BERT embeddings for a large text dataset (Bengali/English) efficiently.

An easy-to-use Python module that helps you to extract the BERT embeddings for a large text dataset (Bengali/English) efficiently.

Khalid Saifullah 37 Sep 05, 2022
Datasets of Automatic Keyphrase Extraction

This repository contains 20 annotated datasets of Automatic Keyphrase Extraction made available by the research community. Following are the datasets and the original papers that proposed them. If yo

LIAAD - Laboratory of Artificial Intelligence and Decision Support 163 Dec 23, 2022
A NLP program: tokenize method, PoS Tagging with deep learning

IRIS NLP SYSTEM A NLP program: tokenize method, PoS Tagging with deep learning Report Bug · Request Feature Table of Contents About The Project Built

Zakaria 7 Dec 13, 2022
Levenshtein and Hamming distance computation

distance - Utilities for comparing sequences This package provides helpers for computing similarities between arbitrary sequences. Included metrics ar

112 Dec 22, 2022
Subtitle Workshop (subshop): tools to download and synchronize subtitles

SUBSHOP Tools to download, remove ads, and synchronize subtitles. SUBSHOP Purpose Limitations Required Web Credentials Installation, Configuration, an

Joe D 4 Feb 13, 2022
GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form

GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.

GNES.ai 1.2k Jan 06, 2023
Crowd sourced training data for Rasa NLU models

NLU Training Data Crowd-sourced training data for the development and testing of Rasa NLU models. If you're interested in grabbing some data feel free

Rasa 169 Dec 26, 2022
This repository serves as a place to document a toy attempt on how to create a generative text model in Catalan, based on GPT-2

GPT-2 Catalan playground and scripts to train a GPT-2 model either from scrath or from another pretrained model.

Laura 1 Jan 28, 2022
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents

Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee

Wenlong Huang 114 Dec 29, 2022
Two-stage text summarization with BERT and BART

Two-Stage Text Summarization Description We experiment with a 2-stage summarization model on CNN/DailyMail dataset that combines the ability to filter

Yukai Yang (Alexis) 6 Oct 22, 2022
Tokenizer - Module python d'analyse syntaxique et de grammaire, tokenization

Tokenizer Le Tokenizer est un analyseur lexicale, il permet, comme Flex and Yacc par exemple, de tokenizer du code, c'est à dire transformer du code e

Manolo 1 Aug 15, 2022
Ceaser-Cipher - The Caesar Cipher technique is one of the earliest and simplest method of encryption technique

Ceaser-Cipher The Caesar Cipher technique is one of the earliest and simplest me

Lateefah Ajadi 2 May 12, 2022
Generating new names based on trends in data using GPT2 (Transformer network)

MLOpsNameGenerator Overall Goal The goal of the project is to develop a model that is capable of creating Pokémon names based on its description, usin

Gustav Lang Moesmand 2 Jan 10, 2022
Simple program that translates the name of files into English

Simple program that translates the name of files into English. Useful for when editing/inspecting programs that were developed in a foreign language.

0 Dec 22, 2021
Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memories using approximate nearest neighbors, in Pytorch

Memorizing Transformers - Pytorch Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memori

Phil Wang 364 Jan 06, 2023
Utilities for preprocessing text for deep learning with Keras

Note: This utility is really old and is no longer maintained. You should use keras.layers.TextVectorization instead of this. Utilities for pre-process

Hamel Husain 180 Dec 09, 2022
A Python 3.6+ package to run .many files, where many programs written in many languages may exist in one file.

RunMany Intro | Installation | VSCode Extension | Usage | Syntax | Settings | About A tool to run many programs written in many languages from one fil

6 May 22, 2022
DeLighT: Very Deep and Light-Weight Transformers

DeLighT: Very Deep and Light-weight Transformers This repository contains the source code of our work on building efficient sequence models: DeFINE (I

Sachin Mehta 440 Dec 18, 2022
Chinese NewsTitle Generation Project by GPT2.带有超级详细注释的中文GPT2新闻标题生成项目。

GPT2-NewsTitle 带有超详细注释的GPT2新闻标题生成项目 UpDate 01.02.2021 从网上收集数据,将清华新闻数据、搜狗新闻数据等新闻数据集,以及开源的一些摘要数据进行整理清洗,构建一个较完善的中文摘要数据集。 数据集清洗时,仅进行了简单地规则清洗。

logCong 785 Dec 29, 2022