NeuroSense AI

• 

About the Project NeuroSense AI is a simple machine learning project designed to predict Alzheimer’s disease using patient health data. It helps understand which features are most important for early detection and supports decision-making in healthcare.

Inspiration

Alzheimer’s is a growing health challenge worldwide. Early detection can help patients and families plan treatment and care. Inspired to use AI for healthcare, we created NeuroSense AI to make data-driven predictions accessible for beginners and researchers alike.

What it does

Reads patient health datasets

Trains a Random Forest model to predict Alzheimer’s

Shows model accuracy and important health features

Helps visualize which factors contribute most to disease prediction

How we built it

Google Colab for coding and running ML workflow

Pandas to read and handle data

Scikit-learn for model building (Random Forest Classifier)

Matplotlib to plot feature importance

GitHub to host code and track changes

Challenges we ran into

Handling datasets with non-numeric values → solved with pd.get_dummies()

Choosing the right features for the model

Ensuring beginner-friendly workflow with clear outputs

Accomplishments that we're proud of

Built a fully functional ML model for Alzheimer’s prediction

Visualized top features that influence the model

Created a step-by-step beginner-friendly Colab notebook

Successfully tested the model and calculated accuracy

What we learned

How to preprocess data and handle categorical variables

How to train and evaluate a machine learning model

Importance of visualizing model results for better understanding

How to make a simple yet functional ML project for healthcare

What's next for NeuroSense AI

Expand the dataset to include more features for better prediction

Add a web interface for interactive predictions

Explore other ML models to improve accuracy

Collaborate with healthcare professionals for real-world testing

Built With

• csv
• github
• google-colab
• jupyter
• matplotlib
• pandas
• python
• scikit-learn