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Chest X-rays (CXRs) play an integral role in driving critical decisions in disease management and patient care.
Chexnet: radiologist-level pneumonia detection on chest x-rays with deep learning
Yang, H. M., Duan, T., Ding, D., Bagul, A., Langlotz, C., Shpanskaya, K., et al · 2017
Earlier work this paper cites.
Pyramid scene parsing network, 2017
Zhao, H., Shi, J., Qi, X., Wang, X., and Jia, J · 2017
Earlier work this paper cites.
Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison, 2019
Irvin, J., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R., Shpanskaya, K., Seekins, J., Mong, D. A., Halabi, S. S., Sandberg, J. K., Jones, R., Larson, D. B., Langlotz, C. P., Patel, B. N., Lungren, M. P., and Ng, A. Y · 2019
Earlier work this paper cites.
Interpretation and documentation of chest x-rays in the acute medical unit
Bahl, S., Ramzan, T., and Maraj, R · 2020
Earlier work this paper cites.
On the limits of cross-domain generalization in automated x-ray prediction
Cohen, J. P., Hashir, M., Brooks, R., and Bertrand, H · 2020
Earlier work this paper cites.
Smart chest x-ray worklist prioritization using artificial intelligence: a clinical workflow simulation
Baltruschat, I., Steinmeister, L., Nickisch, H., Saalbach, A., Grass, M., Adam, G., Knopp, T., and Ittrich, H · 2021
Earlier work this paper cites.
A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentation
Lian, J., Liu, J., Zhang, S., Gao, K., Liu, X., Zhang, D., and Yu, Y · 2021
Earlier work this paper cites.
Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering, 2021
Liu, B., Zhan, L.-M., Xu, L., Ma, L., Yang, Y., and Wu, X.-M · 2021
Earlier work this paper cites.
Association of artificial intelligence–aided chest radiograph interpretation with reader performance and efficiency
Ahn, J. S., Ebrahimian, S., McDermott, S., Lee, S., Naccarato, L., Di Capua, J. F., Wu, M. Y., Zhang, E. W., Muse, V., Miller, B., et al · 2022
Earlier work this paper cites.
Roentgen: Vision-language foundation model for chest x-ray generation, 2022
Chambon, P., Bluethgen, C., Delbrouck, J.-B., der Sluijs, R. V., Połacin, M., Chaves, J. M. Z., Abraham, T. M., Purohit, S., Langlotz, C. P., and Chaudhari, A · 2022
Earlier work this paper cites.
TorchXRayVision: A library of chest X-ray datasets and models
Cohen, J. P., Viviano, J. D., Bertin, P., Morrison, P., Torabian, P., Guarrera, M., Lungren, M. P., Chaudhari, A., Brooks, R., Hashir, M., and Bertrand, H · 2022
Earlier work this paper cites.
An accurate and explainable deep learning system improves interobserver agreement in the interpretation of chest radiograph
Pham, H. H., Nguyen, H. Q., Nguyen, H. T., Le, L. T., and Khanh, L · 2022
Earlier work this paper cites.
Sources, Effects and Risks of Ionizing Radiation: UNSCEAR 2020/2021 Report, Volume I
United Nations Scientific Committee on the Effects of Atomic Radiation · 2022
Earlier work this paper cites.
Integration and implementation strategies for ai algorithm deployment with smart routing rules and workflow management, 2023
Erdal, B. S., Gupta, V., Demirer, M., Fair, K. H., White, R. D., Blair, J., Deichert, B., Lafleur, L., Qin, M. M., Bericat, D., and Genereaux, B · 2023
Earlier work this paper cites.
Generative artificial intelligence for chest radiograph interpretation in the emergency department
Huang, J., Neill, L., Wittbrodt, M., Melnick, D., Klug, M., Thompson, M., Bailitz, J., Loftus, T., Malik, S., Phull, A., et al · 2023
Earlier work this paper cites.
Swe-bench: Can language models resolve real-world github issues?
Jimenez, C. E., Yang, J., Wettig, A., Yao, S., Pei, K., Press, O., and Narasimhan, K · 2023
Earlier work this paper cites.
Segment anything, 2023
Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., Dollár, P., and Girshick, R · 2023
Earlier work this paper cites.
Agentbench: Evaluating llms as agents
Liu, X., Yu, H., Zhang, H., Xu, Y., Lei, X., Lai, H., Gu, Y., Ding, H., Men, K., Yang, K., et al · 2023
Cited alongside, same era.
Capabilities of gpt-4 on medical challenge problems
Nori, H., King, N., McKinney, S. M., Carignan, D., and Horvitz, E · 2023
Cited alongside, same era.
Rad-restruct: A novel vqa benchmark and method for structured radiology reporting, 2023
Pellegrini, C., Keicher, M., Özsoy, E., and Navab, N · 2023
Cited alongside, same era.
The impact of artificial intelligence on the reading times of radiologists for chest radiographs
Shin, H. J., Han, K., Ryu, L., and Kim, E.-K · 2023
Cited alongside, same era.
Towards generalist biomedical ai, 2023
Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., Mustafa, B., Chowdhery, A., Liu, Y., Kornblith, S., Fleet, D., Mansfield, P., Prakash, S., Wong, R., Virmani, S., Semturs, C., Mahdavi, S. S., Green, B., Dominowska, E., y Arcas, B. A., Barral, J., Webster, D., Corrado, G. S., Matias, Y., Singhal, K., Florence, P., Karthikesalingam, A., and Natarajan, V · 2023
Mdagents: An adaptive collaboration of llms for medical decision-making
Kim, Y., Park, C., Jeong, H., Chan, Y. S., Xu, X., McDuff, D., Lee, H., Ghassemi, M., Breazeal, C., and Park, H. W · 2024
Later among the works it cites.
The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey
Masterman, T., Besen, S., Sawtell, M., and Chao, A · 2024
Later among the works it cites.
Chestbiox-gen: contextual biomedical report generation from chest x-ray images using biogpt and co-attention mechanism
Ouis, M. Y. and Akhloufi, M. A · 2024
Later among the works it cites.
M4cxr: Exploring multi-task potentials of multi-modal large language models for chest x-ray interpretation, 2024
Park, J., Kim, S., Yoon, B., Hyun, J., and Choi, K · 2024
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Agentclinic: a multimodal agent benchmark to evaluate ai in simulated clinical environments, 2024
Schmidgall, S., Ziaei, R., Harris, C., Reis, E., Jopling, J., and Moor, M · 2024
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Cited alongside, same era.
Towards generalist foundation model for radiology by leveraging web-scale 2d and 3d medical data, 2023
Wu, C., Zhang, X., Zhang, Y., Wang, Y., and Xie, W · 2023
Cited alongside, same era.
Multimodal chatgpt for medical applications: an experimental study of gpt-4v
Yan, Z., Zhang, K., Zhou, R., He, L., Li, X., and Sun, L · 2023
Cited alongside, same era.
React: Synergizing reasoning and acting in language models, 2023
Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., and Cao, Y · 2023
Cited alongside, same era.
An in-depth survey of large language model-based artificial intelligence agents
Zhao, P., Jin, Z., and Cheng, N · 2023
Cited alongside, same era.
Maira-2: Grounded radiology report generation, 2024
Bannur, S., Bouzid, K., Castro, D. C., Schwaighofer, A., Thieme, A., Bond-Taylor, S., Ilse, M., Pérez-García, F., Salvatelli, V., Sharma, H., Meissen, F., Ranjit, M., Srivastav, S., Gong, J., Codella, N. C. F., Falck, F., Oktay, O., Lungren, M. P., Wetscherek, M. T., Alvarez-Valle, J., and Hyland, S. L · 2024
Cited alongside, same era.
Medmax: Mixed-modal instruction tuning for training biomedical assistants, 2024
Bansal, H., Israel, D., Zhao, S., Li, S., Nguyen, T., and Grover, A · 2024
Cited alongside, same era.
Chexpert plus: Augmenting a large chest x-ray dataset with text radiology reports, patient demographics and additional image formats, 2024
Chambon, P., Delbrouck, J.-B., Sounack, T., Huang, S.-C., Chen, Z., Varma, M., Truong, S. Q., Chuong, C. T., and Langlotz, C. P · 2024
Cited alongside, same era.
Later among the works it cites.
Collaboration between clinicians and vision–language models in radiology report generation
Tanno, R., Barrett, D. G., Sellergren, A., Ghaisas, S., Dathathri, S., See, A., Welbl, J., Lau, C., Tu, T., Azizi, S., et al · 2024
Later among the works it cites.
Mmau: A holistic benchmark of agent capabilities across diverse domains
Yin, G., Bai, H., Ma, S., Nan, F., Sun, Y., Xu, Z., Ma, S., Lu, J., Kong, X., Zhang, A., et al · 2024
Later among the works it cites.
Zambrano Chaves, J., Huang, S.-C., Xu, Y., Xu, H., Usuyama, N., and Zhang, S, e. a · 2024
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Recent advances, applications and open challenges in machine learning for health: Reflections from research roundtables at ml4h 2024 symposium, 2025
Adibi, A., Cao, X., Ji, Z., Kaur, J. N., Chen, W., Healey, E., Nuwagira, B., Ye, W., Woollard, G., Xu, M. A., Cui, H., Xi, J., Chang, T., Bikia, V., Zhang, N., Noori, A., Xia, Y., Hossain, M. B., Frank, H. A., Peluso, A., Pu, Y., Shen, S. Z., Wu, J., Fallahpour, A., Mahbub, S., Duncan, R., Zhang, Y., Cao, Y., Xu, Z., Craig, M., Krishnan, R. G., Beheshti, R., Rehg, J. M., Karim, M. E., Coffee, M., Celi, L. A., Fries, J. A., Sadatsafavi, M., Shung, D., McWeeney, S., Dafflon, J., and Jabbour, S · 2025
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Advancing medical representation learning through high-quality data, 2025
Baghbanzadeh, N., Fallahpour, A., Parhizkar, Y., Ogidi, F., Roy, S., Ashkezari, S., Khazaie, V. R., Colacci, M., Etemad, A., Afkanpour, A., and Dolatabadi, E · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Guo, D., Yang, D., Zhang, H., Song, J., Zhang, R., Xu, R., Zhu, Q., Ma, S., Wang, P., Bi, X., et al · 2025
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Medagentbench: Dataset for benchmarking llms as agents in medical applications, 2025
Jiang, Y., Black, K. C., Geng, G., Park, D., Ng, A. Y., and Chen, J. H · 2025
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Medsam2: Segment anything in 3d medical images and videos, 2025
Ma, J., Yang, Z., Kim, S., Chen, B., Baharoon, M., Fallahpour, A., Asakereh, R., Lyu, H., and Wang, B · 2025
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Radialog: A large vision-language model for radiology report generation and conversational assistance, 2025
Pellegrini, C., Özsoy, E., Busam, B., Navab, N., and Keicher, M · 2025
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The rise and potential of large language model based agents: A survey
Xi, Z., Chen, W., Guo, X., He, W., Ding, Y., Hong, B., Zhang, M., Wang, J., Jin, S., Zhou, E., et al · 2025
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Segment anything in medical images
Ma, J., He, Y., Li, F., Han, L., You, C., and Wang, B · 2041
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