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Congress: ECR25
Poster Number: C-21211
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-21211
Authorblock: C. R. Q. Lee, G. Lip; Aberdeen/UK
Disclosures:
Charlotte Ruo Qi Lee: Nothing to disclose
Gerald Lip: Nothing to disclose
Keywords: Breast, Mammography, MR, Ultrasound, Computer Applications-General, Technology assessment, Cancer, Multidisciplinary cancer care, Quality assurance, Sustainability
References

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2. Bhayana R. Chatbots and large language models in radiology: A practical primer for clinical and research applications. Radiology. 2024;310(1). doi: 10.1148/radiol.232756.

3. Ke Y, Jin L, Elangovan K, Abdullah HR, Liu N, Sia AT, Soh CR, Tung JY, Ong JC, Ting DS. Development and testing of retrieval augmented generation in large language models--a case study report. arXiv preprint arXiv:2402.01733. 2024 Jan 29.

4. Doo FX, et al. Environmental sustainability and AI in radiology: A double-edged sword. Radiology. 2024;310(2). doi: 10.1148/radiol.232030.

5. Ligozat A-L, Lefevre J, Bugeau A, Combaz J. Unraveling the hidden environmental impacts of AI solutions for environment life cycle assessment of AI solutions. Sustainability. 2022;14:5172. doi: 10.3390/su14095172.

 

 
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