Code used for the papers:
Preprint: A Critical Analysis Of Nlp and Clinical Correctness Metrics to Measure Progress on X-Ray Report Generation. Pablo Pino, Denis Parra, Jocelyn Dunstan, and Cecilia Besa Submitted to Artificial Intelligence in Medicine (AIM) Available at SSRN: https://ssrn.com/abstract=4052411 or http://dx.doi.org/10.2139/ssrn.4052411
Clinically Correct Report Generation from Chest X-rays using Templates \ Pablo Pino, Denis Parra, Cecilia Besa and Claudio Lagos \ MLMI at MICCAI 2021, oral presentation, best paper candidate \ Links: Pre-print, video (10 min), slides, poster
Inspecting state of the art performance and NLP metrics in image-based medical report generation \ Pablo Pino, Denis Parra, Pablo Messina, Cecilia Besa and Sergio Uribe \ LXAI at NeurIPS 2020 \ Links: Poster
And master thesis:
Report generation from chest X-Rays: analysis of NLP metrics and clinically correct template-based model \ Pablo Pino \ Advisor: Denis Parra \ Computer Science Department at PUC Chile
@InProceedings{pino2021clinically,
author="Pino, Pablo
and Parra, Denis
and Besa, Cecilia
and Lagos, Claudio",
editor="Lian, Chunfeng
and Cao, Xiaohuan
and Rekik, Islem
and Xu, Xuanang
and Yan, Pingkun",
title="Clinically Correct Report Generation from Chest X-Rays Using Templates",
booktitle="Machine Learning in Medical Imaging",
year="2021",
publisher="Springer International Publishing",
address="Cham",
pages="654--663",
isbn="978-3-030-87589-3",
}
@article{pino2020inspecting,
title={Inspecting state of the art performance and {NLP} metrics in image-based medical report generation},
author={Pino, Pablo and Parra, Denis and Messina, Pablo and Besa, Cecilia and Uribe, Sergio},
journal={arXiv preprint arXiv:2011.09257},
year={2020},
note={{I}n LXAI at NeurIPS 2020}
}
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