metadata

title: VQA Kalbe Bangkit
emoji: 🏆
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.31.5
app_file: app.py
pinned: false

Kalbe Farma - Visual Question Answering (VQA) for Medical Imaging

Overview

The project addresses the challenge of accurate and efficient medical imaging analysis in healthcare, aiming to reduce human error and workload for radiologists. The proposed solution involves developing advanced AI models for Visual Question Answering (VQA) to assist healthcare professionals in analyzing medical images quickly and accurately. These models will be integrated into a user-friendly web application, providing a practical tool for real-world healthcare settings.

Dataset

The model is trained using the Hugging face.

Reference: ScienceDirect

Model Architecture

The model uses a Parameterized Hypercomplex Shared Encoder network (PHYSEnet).

Reference: ScienceDirect

Demo

Please select the example below or upload 4 pairs of mammography exam results.

Usage

cd src

Run the following command on below
Python app.py

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference