The problem Minds Matter solves

In today's fast-paced and digitally interconnected world, mental health concerns are prevalent, yet often overlooked. This project addresses the critical need for accessible and accurate mental health assessments. The Random Forest classification model employed here is designed to analyze user-provided input and identify potential signs of depression. By offering timely and reliable insights, this tool aims to empower individuals to seek appropriate support and interventions, ultimately leading to a healthier, happier society. Through this project, we strive to contribute to a more proactive approach to mental well-being, leveraging the power of AI and machine learning in the process.

The Random Forest classification model, with its ability to discern complex patterns in user-provided text, serves as a robust tool for mental health assessment. By continuously training and fine-tuning the model on a diverse dataset, we aim to improve its accuracy and sensitivity in identifying potential signs of depression.

Additionally, incorporating natural language processing techniques and sentiment analysis could further enhance the model's capabilities. Regular updates and feedback loops with mental health professionals would ensure the system remains aligned with evolving diagnostic criteria and best practices.

Furthermore, establishing partnerships with mental health organizations and institutions would facilitate the collection of more extensive and diverse datasets, ultimately leading to a more comprehensive and effective tool for mental health assessment. Through continuous refinement and collaboration, we aspire to make a meaningful impact on mental well-being in today's society.

Challenges we ran into

We ran into some problems where we could not fetch the ML model data from our website. The problem is that we are running our python code in Google Colab. The website that is supposed to fetch user input for ML model to predict its values was made using Streamlit API. the code for website is running but the URL provided by the API time out because it is resource heavy and Google Colab free version only supports a particular level of processing. The link for the Google Colab that runs this website successfully is provided below-
https://colab.research.google.com/drive/14d-vmuGt-mRyPUFqch-nytNmWd_Vno6z#scrollTo=xIaY4VD4bdIw
The links provided by the API after running all code cells do not load because the ML Model is heavy for Google Colab and it is not able to render the websites.