https://github.com/linhaowei1/gdcurer
❤️ GDCurer: An AI-assisted Drug Dosage Prediction System for Graves' Disease
https://github.com/linhaowei1/gdcurer
ai4medicine ai4sci clinical-data lifelong-learning weak-supervision
Last synced: 6 months ago
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❤️ GDCurer: An AI-assisted Drug Dosage Prediction System for Graves' Disease
- Host: GitHub
- URL: https://github.com/linhaowei1/gdcurer
- Owner: linhaowei1
- License: apache-2.0
- Created: 2023-08-01T16:29:29.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-01T07:47:37.000Z (about 1 year ago)
- Last Synced: 2024-04-01T21:22:34.307Z (about 1 year ago)
- Topics: ai4medicine, ai4sci, clinical-data, lifelong-learning, weak-supervision
- Language: JavaScript
- Homepage:
- Size: 2.96 MB
- Stars: 6
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# GDCurer: An AI-assisted Drug Dosage Prediction System for Graves' Disease
This repository contains the code for our paper [GDCurer: An AI-assisted Drug Dosage Prediction System for Graves' Disease](#) by [Haowei Lin](https://linhaowei1.github.io), Zhao Chen, Jianhua Zhu, Wenpeng Huang, Ritai Na, Yongkang Qiu, Jing Zhao, Sichen Yin, Xiaodong Li, Rongfu Wang, [Jianzhu Ma](https://majianzhu.com), Lei Kang.
## Quick Links
- [Overview](#overview)
- [Requirements](#requirements)
- [GDCurer Training](#gdcurer-training)
- [Data](#data)
- [Standard Training Experiments](#standard-training-experiments)
- [Lifelong Training Experiments](#lifelong-training-experiments)
- [GDCurer Web App](#gdcurer-web-app)
- [Bugs or Questions?](#bugs-or-questions)
- [Citation](#citation)
## Overview
We propose an AI-assisted drug dosage prediction system for Graves' Disease. GDCurer is capable of predicting the optimal dosage of idonine-131 (I-131) by leveraging the patient's thyroid scintigraph (TS), iodine uptake (IU) information, and the half-life of I-131 (HL). To address the issue of lacking accurate drug dosages in the training data due to the bias introduced by clinicans, a novel machine learning method is developed to exploit the treatment information to correct the bias. Furthermore, GDCurer is designed as a lifelong learner which can continously learn from new clinical data by incorporating the techniques of experience replay (ER) and feature distillation (FD).
## Requirements
First, install PyTorch by following the instructions from [the official website](https://pytorch.org). To faithfully reproduce our results, please use the correct `1.8` version corresponding to your platforms/CUDA versions. PyTorch version higher than `1.8` should also work. For example, if you use Linux and **CUDA11.1** ([how to check CUDA version](https://varhowto.com/check-cuda-version/)), install PyTorch by the following command,
```bash
conda install pytorch==1.8.0 torchvision==0.9.0 cudatoolkit=11.1 -c pytorch -c conda-forge
```
Then run the following script to install the remaining dependencies,
```bash
pip install -r requirements.txt
```
## GDCurer Training
In the following section, we describe how to train GDCurer model by using our code.
### Data
Before training and evaluation, please download the dataset from this [Google Drive link](#) and save them in the `./data` directory.
### Standard Training Experiments
**Training scripts**
We provide an example training script to run standard training of GDCurer. Symply run
```bash
CUDA_VISIBLE_DEVICES=${your_cuda_device_id} bash scripts/standard.sh
```
For the results in the paper, we use Nvidia Tesla A100 GPUs with CUDA 11. Using different types of devices or different versions of CUDA/other software may lead to slightly different performance.
### Lifelong Training Experiments
To run lifelong learning experiments with 4 training phases, simply run
```bash
CUDA_VISIBLE_DEVICES=${your_cuda_device_id} bash scripts/lifelong.sh
```
## GDCurer Web App
We've built a web app on GDCurer using [Django](https://github.com/django/django) and [MySQL](https://dev.mysql.com/downloads/mysql/). You can build it through the [webUI](./webUI/).
## Bugs or questions?
If you have any questions related to the code or the paper, feel free to email [Haowei](`[email protected]`). If you encounter any problems when using the code, or want to report a bug, you can open an issue. Please try to specify the problem with details so we can help you better and quicker!
## Citation
Please cite our paper if you use GDCurer in your work:
```bibtex
@misc{lin2023gdcurer,
title={GDCurer: An AI-assisted Drug Dosage Prediction System for Graves' Disease},
author={Lin, Haowei and Chen, Zhao and Kang, Lei and Ma, Jianzhu},
year={2023}
}
```