Mama Scan

Mama Scan landing page - dark mode
Mama Scan landing page - light mode
Mama Scan
Sign in/Sign up page
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Add new patient
Cervical Cancer Screening step 1
Cervical Cancer Screening step 1.5
Cervical Cancer Screening step 2
Cervical Cancer Screening step 3
Cervical Cancer Screening step 4
Mama Scan Clinical Guidelines
CHV Dashboard
Patient Dashboard
Referral page
Mma Scan
AI Recommendation
Create New Referral
Urgency and Timeline
AI Risk Assessment
Training Material
M-pesa Integration
T&C
Analytics Dashboard
Payment Plans
Preview
Performance Overview
Health Assistant
Payments Dashboard
Appointment Booking
Daraja Integration

Inspiration

We were motivated by the urgent need to reduce preventable cervical cancer deaths in underserved regions. With AI rapidly transforming healthcare, we saw an opportunity to bridge the gap between communitylevel care and early cancer detection.

What it does

MAMA-SCAN helps community health volunteers collect basic patient data and, using an AI model, instantly assess the risk level for cervical cancer. It then recommends whether the patient should be referred for further testing or treatment.

How we built it

We trained a machine learning model using Python, applying libraries like pandas and numpy to clean and process data. We then integrated the model into a robust web app with a user-friendly interface tailored for use by non-technical health workers.

Technologies used:

Python - Pandas - Numpy - Flask - HTML/CSS

Challenges we ran into

Data availability: It was difficult to find clean, localized clinicaldatasets for cervical cancer.

Balancing simplicity and accuracy: We had to ensure the app was both medically accurate and simple enough for use in the field.

Accomplishments that we're proud of

Achieved high model accuracy with minimal overfitting.
Built a clean, intuitive user interface accessible to non-technical users.

Smooth backend data handling and integration with model output.

What we learned

Teamwork:We learned how to work effectively in an interdisciplinary team (2 medical students, 1 software engineer, 1 computer science student, and 1 biomedical engineering student).
How to communicate technical ideas across different fields.
Importance of user-centered design, especially in public health tools.

What's next for Mama Scan

Integrate imaging and microscopic data (e.g., Pap smear images) to enhance diagnostic accuracy. Pilot the tool in rural counties across Kenya.
Train CHVs and scale for national screening programs.