README.md

metadata

datasets:
  - hongrui/mimic_chest_xray_v_1

🩺 CheXNet-MedScan-Report-Gen

CheXNet-MedScan-Report-Gen is an image captioning model for generating diagnostic text reports from chest X-ray images. It combines the power of a pretrained CheXNet encoder (based on DenseNet121) and a bidirectional LSTM decoder to produce sequence-based textual descriptions.

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🧠 Model Architecture

• Encoder: DenseNet121 (CheXNet) with classifier removed
• Decoder: Bidirectional LSTM with dropout
• Feature dimension: 1024
• Embedding dimension: 256
• Hidden dimension: 512
• Vocabulary size: 5000
• Dropout: 0.5

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🔧 Usage

You can load the model using the Hugging Face Transformers library:

from transformers import AutoModel, AutoConfig

config = AutoConfig.from_pretrained("khalednabawi11/Chexnet-MedScan-Report-Gen", trust_remote_code=True)
model = AutoModel.from_pretrained("khalednabawi11/Chexnet-MedScan-Report-Gen", config=config, trust_remote_code=True)