Integrating ChatGPT into Secure Hospital Networks: A Case Study on Improving Radiology Report Analysis
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866914996220329984 |
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| author | Kim, Kyungsu Park, Junhyun Langarica, Saul Alkhadrawi, Adham Mahmoud Do, Synho |
| author_facet | Kim, Kyungsu Park, Junhyun Langarica, Saul Alkhadrawi, Adham Mahmoud Do, Synho |
| contents | This study demonstrates the first in-hospital adaptation of a cloud-based AI, similar to ChatGPT, into a secure model for analyzing radiology reports, prioritizing patient data privacy. By employing a unique sentence-level knowledge distillation method through contrastive learning, we achieve over 95% accuracy in detecting anomalies. The model also accurately flags uncertainties in its predictions, enhancing its reliability and interpretability for physicians with certainty indicators. These advancements represent significant progress in developing secure and efficient AI tools for healthcare, suggesting a promising future for in-hospital AI applications with minimal supervision. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_09358 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Integrating ChatGPT into Secure Hospital Networks: A Case Study on Improving Radiology Report Analysis Kim, Kyungsu Park, Junhyun Langarica, Saul Alkhadrawi, Adham Mahmoud Do, Synho Artificial Intelligence Machine Learning This study demonstrates the first in-hospital adaptation of a cloud-based AI, similar to ChatGPT, into a secure model for analyzing radiology reports, prioritizing patient data privacy. By employing a unique sentence-level knowledge distillation method through contrastive learning, we achieve over 95% accuracy in detecting anomalies. The model also accurately flags uncertainties in its predictions, enhancing its reliability and interpretability for physicians with certainty indicators. These advancements represent significant progress in developing secure and efficient AI tools for healthcare, suggesting a promising future for in-hospital AI applications with minimal supervision. |
| title | Integrating ChatGPT into Secure Hospital Networks: A Case Study on Improving Radiology Report Analysis |
| topic | Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2402.09358 |