Problem

Thyroid disorders are common but often go undiagnosed due to a lack of accessible and affordable screening methods. This results in delayed treatment and increased health risks for patients. Aakash research labs recognized the need for an innovative solution to improve thyroid detection rates.

Our team was tasked with developing a cost-effective and efficient method for detecting thyroid disorders that could be easily implemented in low-resource settings.

Learn more about our project here.

Solution

We developed a machine learning algorithm that analyzes ultrasound images of the thyroid gland to detect abnormalities. The algorithm was trained on a large dataset of ultrasound images from patients with known thyroid disorders, allowing it to accurately identify potential issues.

The system is designed to be user-friendly and can be operated by healthcare professionals with minimal training. It also requires minimal equipment, making it ideal for use in low-resource settings where access to advanced medical technology may be limited.

Impact

Increased early detection rates of thyroid disorders by X%
Reduced healthcare costs associated with delayed diagnosis and treatment

"This project has had an incredible impact on improving access to healthcare for underserved populations."

Team

Team Member #1 - Data Scientist
- Built the machine learning model and optimized its accuracy
- Developed the user interface for the system
Team Member #2 - Medical Doctor
- Provided medical expertise and guidance throughout the project
- Assisted with data collection and analysis

Affordable Thyroid Detection via Machine Learning