A simple web app that shows how Watson's Natural Language Classifier (NLC) can classify ICD-10 code. The app is written in Python using the Flask framework and leverages the Watson Developer Cloud Python SDK

ICD-BERT: Multi-label Classification of ICD-10 Codes with BERT (CLEF 2019)

A simple python library for ICD-10-CM codes

A simple python library for ICD-10 codes

Functions to map between ICD-10 terms and PheCodes for UK Biobank hospital electronic health records

This repository includes API to get ICD-10 codes from descriptions. The Model is a transformer based on BERT. The embeddings are being finetuned based on the following paper: https://arxiv.org/abs/1904.03323 .

UMLS to SNOMED CT and ICD-10 mapping tool: A Python script for generating JSON files containing mappings between UMLS CUIs and SNOMED CT or ICD-10 codes using the UMLS Metathesaurus. Supports exact match, broad relations, and parent-child hierarchy mapping methods.

REST API wrappers for ICD10 CM and PCS XML files (Pyramid + Cornice + lxml ) https://pypi.python.org/pypi/pycd10api

ICD-9 to ICD-10 conversion using CMS General Equivalence Mapping (GEM)

A multi-label classifier based on PLM-ICD paper

Unsupervised Feature Selection to Identify Important ICD-10 Codes for Machine Learning

Tools of Utilization and Cost in Healthcare in Python

This experimental application serves an open source large language model Llama-2 that is connect to a streamlit user interface. The user can define a list of custom symptoms or ICD-10 symptoms as input to the LLM. A two-step chain of prompts will output a list of differential diagnoses followed by a list of examinations to workup these diagnoses.

Mapping drug information (DrugBank), side effects (The SIDER Side Effect Resource), and ICD-10 codes.

A simple Python-library for encoding patient diagnoses according to ICD-10 (German Modification)

MyWork

A browser for ICD codes

Convert between ICD-9 codes and ICD-10 codes

This repository contains lookup tables for the ICD-9 and ICD-10 diagnosis codes, in .csv format. It also contains a .csv table which classifies all ICD-9 codes using the ICD-10 codes' index. It includes the scripts to generate these tables, and the raw text which they are created from.