/HealthCare_ChatBot

The Chatbot (HealthBot) will try to solve or provide an answer to health-related issues or queries that the user is asking for. We are implementing NLP and ML to improve the efficiency of the chatbot. Tkinter is used as a frontend, and we are creating a desktop application with the help of Tkinter.

Primary LanguageJupyter Notebook

Healthcare Chatbot

This is a Python-based project for dealing with human symptoms and predicting their possible outcomes.

Project Goal

The primary goal of this project is to forecast the disease so that patients can get the desired output according to their primary symptoms.

Technology used

We used TKinter to create a desktop-based application and Spacy for NLP-based processes like text sentence tokenization and lemmatization, and we used a Huggingface pretrained model to extrat disease names from a given sentence ( or ner processing).

Huggingface

Downloading pre-trained model from Huggingface Model

from transformers import pipeline
PRETRAINED = "raynardj/ner-disease-ncbi-bionlp-bc5cdr-pubmed"
ners = pipeline(task="ner",model=PRETRAINED, tokenizer=PRETRAINED)

Spacy

Download spacy For window, Linux, MacOS

pip install -U pip setuptools wheel
pip install -U spacy
python -m spacy download en_core_web_sm

Installation

Use the package manager pip to install the requirements.txt file package.

pip install -r requirements.txt

Output Image

First opening window

first window

Main Opening Window

Main Window

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.