Results 11 to 20 of about 1,219,864 (384)

Radiology-GPT: A Large Language Model for Radiology [PDF]

arXiv, 2023
We introduce Radiology-GPT, a large language model for radiology. Using an instruction tuning approach on an extensive dataset of radiology domain knowledge, Radiology-GPT demonstrates superior performance compared to general language models such as StableLM, Dolly and LLaMA.
Zheng Liu, Aoxiao Zhong, Yiwei Li, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Peng Shu, Cheng Chen, Sekeun Kim, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, W. Liu, Dinggang Shen, Xiang Li, Quanzheng Li, Tianming Liu   +18 more
arxiv   +3 more sources

Artificial intelligence in radiology

Nature Reviews Cancer, 2018
Ahmed Hosny, Chintan Parmar, John Quackenbush   +2 more
exaly   +2 more sources

Radiology websites: Conventional radiology [PDF]

Indian Journal of Radiology and Imaging, 2008
IK Indrajit
doaj   +4 more sources

RADIOLOGY [PDF]

Neuro-Oncology, 2011
Abstract This chapter discusses radiology in oral and maxillofacial surgery, including Guidelines for dental radiology, Dental radiography, Panoramic radiography, Ultrasonography, Computed Tomography (CT), Cone beam CT, Magnetic Resonance Imaging (MRI), Nuclear medicine imaging and ...
Y. Arakawa, K.-i. Fujimoto, D. Murata, Y. Nakamoto, T. Okada, S. Miyamoto, O. Bahr, P. N. Harter, L. Weise, S.-J. You, M. W. Ronellenfitsch, J. Rieger, J. P. Steinbach, E. Hattingen, O. Bahr, A. Jurcoane, K. Daneshvar, U. Pilatus, M. Mittelbronn, J. P. Steinbach, E. Hattingen, J. Carrillo, D. Bota, J. Handwerker, L. M.-Y. Su, T. Chen, A. Stathopoulos, H. Yu, J. H. Chang, E. H. Kim, S. H. Kim, null Mi, J. Yun, P. Pytel, J. Collins, Y. Choi, R. Lukas, M. Nicholas, R. Colen, R. Jafrani, P. Zinn, R. Colen, O. Ashour, P. Zinn, R. Colen, M. Vangel, D. Gutman, S. Hwang, M. Wintermark, R. Jain, M. Jilwan-Nicolas, J. Chen, P. Raghavan, C. Holder, D. Rubin, E. Huang, J. Kirby, J. Freymann, C. Jaffe, A. Flanders, P. Zinn, R. Colen, O. Ashour, P. Zinn, R. Colen, P. Zinn, S. Dahiya, V. Statsevych, P. Elson, H. Xie, S. Chao, D. Peereboom, G. Stevens, G. Barnett, M. Ahluwalia, M. Daras, S. Karimi, L. Abrey, J. Sanchez, K. Beal, P. Gutin, T. Kaley, C. Grommes, D. Correa, A. Reiner, S. Briggs, A. Omuro, N. Verburg, F. Hoefnagels, P. Pouwels, R. Boellaard, F. Barkhof, O. Hoekstra, P. Wesseling, J. Reijneveld, J. Heimans, P. Vandertop, K. Zwinderman, h. D. W. Hamer, H. Elinzano, F. Kadivar, P. O. Yadav, V. L. Breese, C. L. Jackson, J. E. Donahue, J. L. Boxerman, B. Ellingson, W. Pope, A. Lai, P. Nghiemphu, T. Cloughesy, B. Ellingson, W. Pope, W. Chen, J. Czernin, M. Phelps, A. Lai, P. Nghiemphu, L. Liau, T. Cloughesy, B. Ellingson, K. Leu, A. Tran, W. Pope, A. Lai, P. Nghiemphu, R. Harris, D. Woodworth, T. Cloughesy, B. Ellingson, W. Pope, K. Leu, W. Chen, J. Czernin, M. Phelps, A. Lai, P. Nghiemphu, L. Liau, T. Cloughesy, B. Ellingson, D. Enzmann, W. Pope, A. Lai, P. Nghiemphu, L. Liau, T. Cloughesy, M. Eoli, A. L. Di Stefano, D. Aquino, A. Scotti, E. Anghileri, L. Cuppini, E. Prodi, G. Finocchiaro, M. G. Bruzzone, K. Fujimoto, Y. Arakawa, D. Murata, Y. Nakamoto, T. Okada, S. Miyamoto, N. Galldiks, G. Stoffels, C. Filss, V. Dunkl, M. Rapp, M. Sabel, M. I. Ruge, R. Goldbrunner, N. J. Shah, G. R. Fink, H. H. Coenen, K.-J. Langen, N. Guha-Thakurta, L. Langford, S. Collet, S. Valable, J.-M. Constans, E. Lechapt-Zalcman, S. Roussel, N. Delcroix, M. Bernaudin, A. Abbas, E. Ibazizene, L. Barre, J.-M. Derlon, J.-S. Guillamo, R. Harris, S. Bookheimer, T. Cloughesy, H. Kim, W. Pope, K. Yang, A. Lai, P. Nghiemphu, B. Ellingson, R. Huang, R. Rahman, A. Hamdan, C. Kane   +199 more
  +8 more sources

Cross-modal Memory Networks for Radiology Report Generation [PDF]

Annual Meeting of the Association for Computational Linguistics, 2022
Medical imaging plays a significant role in clinical practice of medical diagnosis, where the text reports of the images are essential in understanding them and facilitating later treatments.
Zhihong Chen, Yaling Shen, Yan Song, Xiang Wan   +3 more
semanticscholar   +1 more source

ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports [PDF]

European Radiology, 2022
Objectives To assess the quality of simplified radiology reports generated with the large language model (LLM) ChatGPT and to discuss challenges and chances of ChatGPT-like LLMs for medical text simplification.
Katharina Jeblick, B. Schachtner, Jakob Dexl, Andreas Mittermeier, A. T. Stüber, Johanna Topalis, Tobias Weber, Philipp Wesp, B. Sabel, J. Ricke, M. Ingrisch   +10 more
semanticscholar   +1 more source

Redefining Radiology: A Review of Artificial Intelligence Integration in Medical Imaging

Diagnostics, 2023
This comprehensive review unfolds a detailed narrative of Artificial Intelligence (AI) making its foray into radiology, a move that is catalysing transformational shifts in the healthcare landscape.
Reabal Najjar
semanticscholar   +1 more source

Generating Radiology Reports via Memory-driven Transformer [PDF]

Conference on Empirical Methods in Natural Language Processing, 2020
Medical imaging is frequently used in clinical practice and trials for diagnosis and treatment. Writing imaging reports is time-consuming and can be error-prone for inexperienced radiologists.
Zhihong Chen, Yan Song, Tsung-Hui Chang, Xiang Wan   +3 more
semanticscholar   +1 more source

Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions

Diagnostic and Interventional Radiology, 2023
With the advent of large language models (LLMs), the artificial intelligence revolution in medicine and radiology is now more tangible than ever. Every day, an increasingly large number of articles are published that utilize LLMs in radiology.
Tugba Akinci D'Antonoli, A. Stanzione, Christian Bluethgen, Federica Vernuccio, L. Ugga, M. Klontzas, Renato Cuocolo, Roberto Cannella, Burak Koçak   +8 more
semanticscholar   +1 more source

Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation [PDF]

Computer Vision and Pattern Recognition, 2021
Automatically generating radiology reports can improve current clinical practice in diagnostic radiology. On one hand, it can relieve radiologists from the heavy burden of report writing; On the other hand, it can remind radiologists of abnormalities and
Fenglin Liu, Xian Wu, Shen Ge, Wei Fan, Yuexian Zou   +4 more
semanticscholar   +1 more source