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README.md

@@ -90,7 +90,7 @@ This model performs **Contextualized Structured Radiology Report Generation (CSR
 - Max images per sample: 2
 
 **Hardware:**
-- GPU: NVIDIA A100 (or equivalent)
+- GPU: NVIDIA H100
 - Training framework: HuggingFace Transformers + PEFT
 
 ## Usage
@@ -167,37 +167,6 @@ Musculoskeletal and Chest Wall:
 - Bilateral rib fractures noted
 ```
 
-## Evaluation
-
-The model is evaluated using standard medical NLG metrics with additional temporal reasoning evaluation:
-
-- **RadGraph F1**: Measures clinical entity and relation extraction accuracy
-- **BLEU**: N-gram overlap with reference reports
-- **ROUGE** (ROUGE-1, ROUGE-2, ROUGE-L): Recall-oriented metrics
-- **BERTScore**: Semantic similarity using contextual embeddings
-- **CheXbert F1**: Clinical accuracy for pathology classification
-- **Temporal consistency**: Evaluation of comparison statements and longitudinal reasoning
-
-For detailed evaluation results, see the paper: [Automated Structured Radiology Report Generation with Rich Clinical Context](https://arxiv.org/abs/2510.00428)
-
-## Limitations
-
-- Trained exclusively on chest X-ray images (not applicable to other imaging modalities)
-- Performance may vary on images from different institutions or imaging protocols
-- May not capture all rare pathologies or edge cases
-- Requires expert radiologist review before clinical use
-- Temporal reasoning accuracy depends on quality of prior study information
-- Should not be used as the sole diagnostic tool
-
-## Ethical Considerations
-
-- **Medical AI Responsibility**: This model generates medical text and must be used responsibly
-- **Human Oversight Required**: All outputs should be reviewed by qualified radiologists
-- **Data Privacy**: Ensure compliance with HIPAA, GDPR, and local healthcare regulations
-- **Bias and Fairness**: Model trained on specific datasets may have biases; validate on diverse populations
-- **Clinical Validation**: Requires thorough validation before any clinical deployment
-- **Longitudinal Data Handling**: Ensure proper patient consent and data governance for temporal data
-
 ## Citation
 
 If you use this model, please cite:
@@ -214,8 +183,8 @@ If you use this model, please cite:
 Also cite the base model:
 ```bibtex
 @article{chen2024chexagent,
-  title={CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation},
-  author={Chen, Zhihong and Varma, Maya and Delbrouck, Jean-Benoit and Paschali, Magdalini and Blankemeier, Louis and Van Veen, Dave and Valanarasu, Jeya Maria Jose and Youssef, Alaa and Cohen, Joseph Paul and Reis, Eduardo Pontes and Tsai, Emily B. and Johnston, Andrew and Olsen, Cameron and Abraham, Tanishq Mathew and Gatidis, Sergios and Chaudhari, Akshay S. and Lungren, Matthew P.},
+  title={Chexagent: Towards a foundation model for chest x-ray interpretation},
+  author={Chen, Zhihong and Varma, Maya and Delbrouck, Jean-Benoit and Paschali, Magdalini and Blankemeier, Louis and Van Veen, Dave and Valanarasu, Jeya Maria Jose and Youssef, Alaa and Cohen, Joseph Paul and Reis, Eduardo Pontes and others},
   journal={arXiv preprint arXiv:2401.12208},
   year={2024}
 }