Fetching the paper…
Reading the bibliography…
Radiology reports are an instrumental part of modern medicine, informing key clinical decisions such as diagnosis and treatment.
A generalization of sampling without replacement from a finite universe
D. G. Horvitz and D. J. Thompson · 1952
Earlier work this paper cites.
PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals
A. L. Goldberger, L. A. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-K. Peng, and H. E. Stanley · 2000
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu · 2002
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
C.-Y. Lin · 2004
Earlier work this paper cites.
Toward best practices in radiology reporting
C. E. Kahn Jr, C. P. Langlotz, E. S. Burnside, J. A. Carrino, D. S. Channin, D. M. Hovsepian, and D. L. Rubin · 2009
Earlier work this paper cites.
Turning a blind eye: the mobilization of radiology services in resource-poor regions
D. S.-R. Maru, R. Schwarz, J. Andrews, S. Basu, A. Sharma, and C. Moore · 2010
Earlier work this paper cites.
CIDEr: Consensus-based image description evaluation
R. Vedantam, C. L. Zitnick, and D. Parikh · 2015
Earlier work this paper cites.
Radiologist shortage leaves patient care at risk, warns royal college
A. Rimmer · 2017
Earlier work this paper cites.
Multimodal machine learning: A survey and taxonomy
T. Baltrušaitis, C. Ahuja, and L.-P. Morency · 2018
Earlier work this paper cites.
Fixing weight decay regularization in Adam
I. Loshchilov and F. Hutter · 2018
Earlier work this paper cites.
Deep multimodal representation learning: A survey
W. Guo, J. Wang, and S. Wang · 2019
Earlier work this paper cites.
The curious case of neural text degeneration
A. Holtzman, J. Buys, L. Du, M. Forbes, and Y. Choi · 2019
Earlier work this paper cites.
CheXpert: A large chest radiograph dataset with uncertainty labels and expert comparison
J. Irvin, P. Rajpurkar, M. Ko, Y. Yu, S. Ciurea-Ilcus, C. Chute, H. Marklund, B. Haghgoo, R. Ball, K. Shpanskaya, et al · 2019
Earlier work this paper cites.
Clinically accurate chest X-ray report generation
G. Liu, T.-M. H. Hsu, M. McDermott, W. Boag, W.-H. Weng, P. Szolovits, and M. Ghassemi · 2019
Earlier work this paper cites.
Baselines for Chest X-ray Report Generation
W. Boag, T.-M. H. Hsu, M. Mcdermott, G. Berner, E. Alesentzer, and P. Szolovits · 2020
Earlier work this paper cites.
Generating radiology reports via memory-driven transformer
Z. Chen, Y. Song, T.-H. Chang, and X. Wan · 2020
Earlier work this paper cites.
How to create a great radiology report
M. P. Hartung, I. C. Bickle, F. Gaillard, and J. P. Kanne · 2020
Cited alongside, same era.
How the FDA regulates AI
H. B. Harvey and V. Gowda · 2020
Cited alongside, same era.
On faithfulness and factuality in abstractive summarization
J. Maynez, S. Narayan, B. Bohnet, and R. McDonald · 2020
Cited alongside, same era.
CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest X-rays in patients with HIV
P. Rajpurkar, C. O’Connell, A. Schechter, N. Asnani, J. Li, A. Kiani, R. L. Ball, M. Mendelson, G. Maartens, D. J. van Hoving, et al · 2020
Cited alongside, same era.
2020 ACR Data Science institute artificial intelligence survey
B. Allen, S. Agarwal, L. Coombs, C. Wald, and K. Dreyer · 2021
Cited alongside, same era.
Improving radiology report generation systems by removing hallucinated references to non-existent priors
V. Ramesh, N. A. Chi, and P. Rajpurkar · 2022
Later among the works it cites.
Evaluating progress in automatic chest X-ray radiology report generation
F. Yu, M. Endo, R. Krishnan, I. Pan, A. Tsai, E. P. Reis, E. K. U. N. Fonseca, H. M. H. Lee, Z. S. H. Abad, A. Y. Ng, et al · 2022
Later among the works it cites.
Combining human expertise with artificial intelligence: experimental evidence from radiology
N. Agarwal, A. Moehring, P. Rajpurkar, and T. Salz · 2023
Closest in time.
Learning to exploit temporal structure for biomedical vision-language processing
S. Bannur, S. Hyland, Q. Liu, F. Perez-Garcia, M. Ilse, D. C. Castro, B. Boecking, H. Sharma, K. Bouzid, A. Thieme, et al · 2023
Closest in time.
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
K. Dvijotham, J. Winkens, M. Barsbey, S. Ghaisas, R. Stanforth, N. Pawlowski, P. Strachan, Z. Ahmed, S. Azizi, Y. Bachrach, et al · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M. Endo, R. Krishnan, V. Krishna, A. Y. Ng, and P. Rajpurkar · 2021
Cited alongside, same era.
Perceiver io: A general architecture for structured inputs & outputs
A. Jaegle, S. Borgeaud, J.-B. Alayrac, C. Doersch, C. Ionescu, D. Ding, S. Koppula, D. Zoran, A. Brock, E. Shelhamer, et al · 2021
Cited alongside, same era.
RadGraph: Extracting clinical entities and relations from radiology reports
S. Jain, A. Agrawal, A. Saporta, S. Q. Truong, D. N. Duong, T. Bui, P. Chambon, Y. Zhang, M. P. Lungren, A. Y. Ng, et al · 2021
Cited alongside, same era.
Improving factual completeness and consistency of image-to-text radiology report generation
Y. Miura, Y. Zhang, E. Tsai, C. Langlotz, and D. Jurafsky · 2021
Cited alongside, same era.
Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19
Z. Nabulsi, A. Sellergren, S. Jamshy, C. Lau, E. Santos, A. P. Kiraly, W. Ye, J. Yang, R. Pilgrim, S. Kazemzadeh, et al · 2021
Cited alongside, same era.
Effect of a comprehensive deep-learning model on the accuracy of chest X-ray interpretation by radiologists: a retrospective, multireader multicase study
J. C. Seah, C. H. Tang, Q. D. Buchlak, X. G. Holt, J. B. Wardman, A. Aimoldin, N. Esmaili, H. Ahmad, H. Pham, J. F. Lambert, et al · 2021
Cited alongside, same era.
Weakly Supervised Contrastive Learning for Chest X-Ray Report Generation
A. Yan, Z. He, X. Lu, J. Du, E. Chang, A. Gentili, J. McAuley, and C.-n. Hsu · 2021
Cited alongside, same era.
Generative artificial intelligence for chest radiograph interpretation in the emergency department
J. Huang, L. Neill, M. Wittbrodt, D. Melnick, M. Klug, M. Thompson, J. Bailitz, T. Loftus, S. Malik, A. Phull, et al · 2023
Closest in time.
RadGraph2: Modeling disease progression in radiology reports via hierarchical information extraction, 2023
S. Khanna, A. Dejl, K. Yoon, Q. H. Truong, H. Duong, A. Saenz, and P. Rajpurkar · 2023
Closest in time.
The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States
M. Milam and C. Koo · 2023
Closest in time.
Med-Flamingo: a multimodal medical few-shot learner
M. Moor, Q. Huang, S. Wu, M. Yasunaga, C. Zakka, Y. Dalmia, E. P. Reis, P. Rajpurkar, and J. Leskovec · 2023
Closest in time.
Improving chest X-ray report generation by leveraging warm starting
A. Nicolson, J. Dowling, and B. Koopman · 2023
Closest in time.
Perception test: A diagnostic benchmark for multimodal video models
V. Pătrăucean, L. Smaira, A. Gupta, A. R. Continente, L. Markeeva, D. Banarse, S. Koppula, J. Heyward, M. Malinowski, Y. Yang, et al · 2023
Closest in time.
The current and future state of AI interpretation of medical images
P. Rajpurkar and M. P. Lungren · 2023
Closest in time.
Interactive and explainable region-guided radiology report generation
T. Tanida, P. Müller, G. Kaissis, and D. Rueckert · 2023
Closest in time.
Towards generalist biomedical AI
T. Tu, S. Azizi, D. Driess, M. Schaekermann, M. Amin, P.-C. Chang, A. Carroll, C. Lau, R. Tanno, I. Ktena, B. Mustafa, A. Chowdhery, Y. Liu, S. Kornblith, D. Fleet, P. Mansfield, S. Prakash, R. Wong, S. Virmani, C. Semturs, S. S. Mahdavi, B. Green, E. Dominowska, B. A. y Arcas, J. Barral, D. Webster, G. S. Corrado, Y. Matias, K. Singhal, P. Florence, A. Karthikesalingam, and V. Natarajan · 2023
Closest in time.
Style-aware radiology report generation with RadGraph and few-shot prompting
B. Yan, R. Liu, D. E. Kuo, S. Adithan, E. P. Reis, S. Kwak, V. K. Venugopal, C. P. O’Connell, A. Saenz, P. Rajpurkar, et al · 2023
Closest in time.