CA-Eye Application
Early detection of cancer by analyzing medical images and scans using deep learning models.
Timeline
Feb 2024
Sector
Health
Role
Mobile Developer
Tools
Kotlin, AI Model
Context
What's CA-Eye?
Cancer remains a leading cause of death worldwide, and early detection is crucial for improving treatment outcomes. However, traditional diagnostic methods can be invasive, expensive, and may not be accessible to everyone. Additionally, there is a lack of standardized tools to help healthcare professionals quickly assess cancer risk from medical images.
Problem Statement
Situation: Doctors often struggle to quickly determine the severity of a patient's cancer from medical images, leading to delays in treatment decisions. Additionally, there are limited accessible tools that can provide immediate risk assessments, especially in areas with limited specialist access. This can result in delayed treatment and poorer patient outcomes.
The Process & Workflow
Task & Action: The primary objective was to deploy a seamless mobile ecosystem that allowed users to upload clinical images for early risk assessment and access trusted medical articles. The project was divided into essential development phases:
Mobile App Development
We set out to develop an intuitive mobile and web ecosystem that allowed doctors to quickly upload patient images and receive immediate AI-powered risk assessments. The platform was designed to streamline the diagnostic workflow, enabling faster treatment decisions and improving patient outcomes.
Key Features
AI Cancer Photo Analysis
Allows users to upload or take a photo of medical scans or skin lesions to get instant, deep-learning-powered cancer risk insights.
Curated Health News
Provides a dedicated feed of validated medical articles, cancer prevention tips, and the latest research updates.
Lesson Learned
Developing CA-Eye reinforced the crucial importance of bridging cutting-edge AI models with an incredibly intuitive user experience. Since medical screening tools carry significant emotional weight, features like image analysis and article feeds had to be delivered with high clarity, responsiveness, and clean layout design to build trust and empower users effectively.