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index.html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>VQA Kalbe Bangkit</title>
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<style>
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body {
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font-family: Arial, sans-serif;
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background: linear-gradient(to right, blue, purple);
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color: white;
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text-align: center;
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padding: 20px;
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}
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.container {
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max-width: 800px;
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margin: 0 auto;
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background: rgba(255, 255, 255, 0.1);
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padding: 20px;
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border-radius: 10px;
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}
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.container img {
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max-width: 100%;
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height: auto;
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}
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pre {
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text-align: left;
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background: rgba(0, 0, 0, 0.7);
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padding: 10px;
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border-radius: 5px;
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overflow-x: auto;
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}
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a {
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color: #00e6e6;
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text-decoration: none;
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}
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a:hover {
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text-decoration: underline;
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}
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</style>
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</head>
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<body>
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<div class="container">
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<h1>Kalbe Farma - Visual Question Answering (VQA) for Medical Imaging</h1>
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<h2>Overview</h2>
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<p>
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The project addresses the challenge of accurate and efficient medical imaging analysis in healthcare, aiming to reduce human error and workload for radiologists.
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The proposed solution involves developing advanced AI models for Visual Question Answering (VQA) to assist healthcare professionals in analyzing medical images
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quickly and accurately. These models will be integrated into a user-friendly web application, providing a practical tool for real-world healthcare settings.
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</p>
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<h2>Dataset</h2>
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<p>
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The model is trained using the <a href="https://huggingface.co/datasets/flaviagiammarino/vqa-rad/viewer" target="_blank">Hugging face</a>.
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</p>
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<p>Reference: <a href="https://www.sciencedirect.com/science/article/abs/pii/S0933365723001252" target="_blank">ScienceDirect</a></p>
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<h2>Model Architecture</h2>
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<p>
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The model uses a Parameterized Hypercomplex Shared Encoder network (PHYSEnet).
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</p>
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<img src="path/to/your/image.png" alt="Model Architecture">
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<p>Reference: <a href="https://www.sciencedirect.com/science/article/abs/pii/S0933365723001252" target="_blank">ScienceDirect</a></p>
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<h2>Demo</h2>
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<p>
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Please select the example below or upload 4 pairs of mammography exam results.
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</p>
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<h2>Usage</h2>
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<pre>
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<code>
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cd src
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Run the following command below:
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python app.py
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</code>
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</pre>
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<p>Check out the configuration reference at <a href="https://huggingface.co/docs/hub/spaces-config-reference" target="_blank">Hugging Face</a></p>
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</div>
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</body>
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</html>
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