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📃: Add medicine prediction system #249

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ishakatiyar06 opened this issue Oct 7, 2024 · 2 comments · Fixed by #286
Closed

📃: Add medicine prediction system #249

ishakatiyar06 opened this issue Oct 7, 2024 · 2 comments · Fixed by #286
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Contributor Denotes issues or PRs submitted by contributors to acknowledge their participation. gssoc-ext hacktoberfest level2 Status: Assigned💻 Indicates an issue has been assigned to a contributor.

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@ishakatiyar06
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🔴 Title : medicine prediction system
🔴 Aim :
🔴 Brief Explanation : Medicine Prediction System is an innovative healthcare web application designed to assist users in predicting potential health issues based on their symptoms. . Users can input their symptoms, which the system analyzes to provide potential medical conditions.
WeCare Medicine Prediction System is built using the following tech stack:

Frontend:

HTML
CSS
JavaScript
Backend:

Python (Flask framework)
Database:

MongoDB

Screenshots 📷

N/A

To be Mentioned while taking the issue :

  • Full name : Isha Katiyar
  • What is your participant role? (Mention the Open Source Program name. Eg. GSOC, GSSOC, SSOC, JWOC, etc.)
    GSSOC

Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

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github-actions bot commented Oct 7, 2024

🙌 Thank you for bringing this issue to our attention! We appreciate your input and will investigate it as soon as possible.

Feel free to join our community on Discord to discuss more!

@UTSAVS26 UTSAVS26 added Contributor Denotes issues or PRs submitted by contributors to acknowledge their participation. Status: Assigned💻 Indicates an issue has been assigned to a contributor. level2 gssoc-ext hacktoberfest labels Oct 8, 2024
UTSAVS26 added a commit that referenced this issue Oct 10, 2024
# Pull Request for PyVerse 💡


## Issue Title : <!-- Enter the issue title here -->Add medicine
prediction system

- **Info about the related issue (Aim of the project)** : <!-- What's
the goal of the project -->
- This project adds a medicine prediction system under the Machine
Learning section. The goal of the system is to predict appropriate
medicines based on user inputs related to symptoms or conditions. This
enhances the machine learning repository with practical healthcare-based
applications.
- **Name:** <!--Mention Your name--> Isha Katiyar
- **GitHub ID:** <!-- Mention your GitHub ID -->ishakatiyar06
- **Email ID:** <!--Mention your email ID for further communication.
-->katiyarisha16@gmail.com
- **Idenitfy yourself: (Mention in which program you are contributing
in. Eg. For a WoB 2024 participant it's, `WoB Participant`)** <!--
Mention in which program you are contributing -->GSSoC-extd 2024


<!-- Mention the following details and these are mandatory -->

Closes: #249 

### Describe the add-ons or changes you've made 📃
I have added a medicine prediction system using an ML model that takes
user input (such as symptoms) and predicts the recommended medicines.
The project includes both the model and the implementation under the
Machine_Learning/WeCare/ folder.

Give a clear description of what have you added or modifications made

## Type of change ☑️

What sort of change have you made:
<!--
Example how to mark a checkbox:-
- [x] My code follows the code style of this project.
-->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Code style update (formatting, local variables)
- [ ] Breaking change (fix or feature that would cause existing
functionality to not work as expected)
- [ ] This change requires a documentation update

## How Has This Been Tested? ⚙️

Describe how it has been tested
Describe how have you verified the changes made
I have tested this feature locally using sample inputs to ensure the
model predicts appropriate medicines. I verified the outputs against
known results to confirm accuracy and stability.

## Checklist: ☑️
<!--
Example how to mark a checkbox:-
- [x] My code follows the code style of this project.
-->
- [x] My code follows the guidelines of this project.
- [x] I have performed a self-review of my own code.
- [x] I have commented my code, particularly wherever it was hard to
understand.
- [x] I have made corresponding changes to the documentation.
- [x] My changes generate no new warnings.
- [x] I have added things that prove my fix is effective or that my
feature works.
- [x] Any dependent changes have been merged and published in downstream
modules.
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