Pranix-Ai

Mascot
AI model Errors
AI model Accuracy
Confidences
Infographic AYURA.AI
Infographic DERM.AI
Infographic DENTRONIX.AI

Inspiration Behind Pranix AI 🧬

We created Pranix AI based on a simple realization: People disregard symptoms until it’s too late. Whether it’s a dental problem, skin disease, or mental ailment. These all have telltale signs way before they reach a problematic stage. But due to various reasons like lack of specialists, social stigma, monetary constraints, and general unawareness, help is often sought too late. Be able to spot early red flags. Provide smart insights to the user. And overall shift healthcare from being reactive to being preventive. We believe AI shouldn’t replace doctors; it should empower them. Pranix AI was built with the goal of aiding and streamlining early detection.

Our primary modules of Pranix AI:

-Tooth Detection (DENTRONIX.AI) -Skin Dermatology Detection (DERM.AI) -Ayurvedic Dosha Analysis (AYURA.AI) -Cortex AI (mapping between neurological and psychological data)

Tech Stack:

Tensorflow model -> (trained with Teachable Machine + manual tweaking) Html + WebView -> For flexible front-end design Firebase -> Storage + handling data Image Processing -> Images are only processed after explicit consent; deletion input was built into preprocessing, and storage was planned accordingly. Model Inference -> Handled securely on the server.

Workflow:

User uploads image -> Image preprocessing -> AI model inference -> Predictions are given a confidence score. -> Results are shown to the user with a corresponding explanation.

Challenges We Overcame

Achieving Model Accuracy with Deployment Simplicity This was difficult as most lightweight model deployment methods weren’t as accurate as we needed. Limitations of No-code platform No-code platforms didn’t allow us to properly integrate our AI models, which is why we migrated to an HTML-centric design. Data Privacy and Responsibility Patient medical imagery can not be handled without verifiable consent, patient-controlled deletion, and secure planning for storage. Garnering trust with clear outputs AI in healthcare needs to be smart at how it communicates with its users. We made sure our outputs were explanatory but not open for misinterpretation.

The Bigger Picture ✨

AI has the opportunity to make healthcare more accessible, especially in the field of early detection. With Pranix AI, we want to expand into: Making preventive healthcare easier Creating an AI-assisted diagnostic platform Building a system for early intervention Hospital should be the last place you go for healthcare. Awareness should be the first.