Zobrazeno 1 - 10
of 1 493
pro vyhledávání: '"Johnston, Andrew A."'
Autor:
Prakash, Eva, Valanarasu, Jeya Maria Jose, Chen, Zhihong, Reis, Eduardo Pontes, Johnston, Andrew, Pareek, Anuj, Bluethgen, Christian, Gatidis, Sergios, Olsen, Cameron, Chaudhari, Akshay, Ng, Andrew, Langlotz, Curtis
Purpose: To explore best-practice approaches for generating synthetic chest X-ray images and augmenting medical imaging datasets to optimize the performance of deep learning models in downstream tasks like classification and segmentation. Materials a
Externí odkaz:
http://arxiv.org/abs/2411.18602
Autor:
Xu, Justin, Chen, Zhihong, Johnston, Andrew, Blankemeier, Louis, Varma, Maya, Hom, Jason, Collins, William J., Modi, Ankit, Lloyd, Robert, Hopkins, Benjamin, Langlotz, Curtis, Delbrouck, Jean-Benoit
Publikováno v:
Proceedings of the 23rd Workshop on Biomedical Natural Language Processing (2024) 85-98
Recent developments in natural language generation have tremendous implications for healthcare. For instance, state-of-the-art systems could automate the generation of sections in clinical reports to alleviate physician workload and streamline hospit
Externí odkaz:
http://arxiv.org/abs/2409.16603
Autor:
Aali, Asad, Johnston, Andrew, Blankemeier, Louis, Van Veen, Dave, Derry, Laura T, Svec, David, Hom, Jason, Boutin, Robert D., Chaudhari, Akshay S.
Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to extract diagnostic information and is an emerging tool for detecting underdiagnosed conditions such as
Externí odkaz:
http://arxiv.org/abs/2409.11686
Autor:
Blankemeier, Louis, Cohen, Joseph Paul, Kumar, Ashwin, Van Veen, Dave, Gardezi, Syed Jamal Safdar, Paschali, Magdalini, Chen, Zhihong, Delbrouck, Jean-Benoit, Reis, Eduardo, Truyts, Cesar, Bluethgen, Christian, Jensen, Malte Engmann Kjeldskov, Ostmeier, Sophie, Varma, Maya, Valanarasu, Jeya Maria Jose, Fang, Zhongnan, Huo, Zepeng, Nabulsi, Zaid, Ardila, Diego, Weng, Wei-Hung, Junior, Edson Amaro, Ahuja, Neera, Fries, Jason, Shah, Nigam H., Johnston, Andrew, Boutin, Robert D., Wentland, Andrew, Langlotz, Curtis P., Hom, Jason, Gatidis, Sergios, Chaudhari, Akshay S.
Over 85 million computed tomography (CT) scans are performed annually in the US, of which approximately one quarter focus on the abdomen. Given the current radiologist shortage, there is a large impetus to use artificial intelligence to alleviate the
Externí odkaz:
http://arxiv.org/abs/2406.06512
Autor:
Chen, Zhihong, Varma, Maya, Delbrouck, Jean-Benoit, Paschali, Magdalini, Blankemeier, Louis, Van Veen, Dave, Valanarasu, Jeya Maria Jose, Youssef, Alaa, Cohen, Joseph Paul, Reis, Eduardo Pontes, Tsai, Emily B., Johnston, Andrew, Olsen, Cameron, Abraham, Tanishq Mathew, Gatidis, Sergios, Chaudhari, Akshay S., Langlotz, Curtis
Chest X-rays (CXRs) are the most frequently performed imaging test in clinical practice. Recent advances in the development of vision-language foundation models (FMs) give rise to the possibility of performing automated CXR interpretation, which can
Externí odkaz:
http://arxiv.org/abs/2401.12208
Artificial intelligence (AI) models are prevalent today and provide a valuable tool for artists. However, a lesser-known artifact that comes with AI models that is not always discussed is the glitch. Glitches occur for various reasons; sometimes, the
Externí odkaz:
http://arxiv.org/abs/2308.08576
Autor:
Zhou, Zhilei, Qiu, Ziyu, Niblett, Brad, Johnston, Andrew, Schwartzentruber, Jeffrey, Zincir-Heywood, Nur, Heywood, Malcolm
Publikováno v:
LNCS, 29 March 2023
An approach to evolutionary ensemble learning for classification is proposed in which boosting is used to construct a stack of programs. Each application of boosting identifies a single champion and a residual dataset, i.e. the training records that
Externí odkaz:
http://arxiv.org/abs/2211.15621
Autor:
Yao, Zhenpeng, Lum, Yanwei, Johnston, Andrew, Mejia-Mendoza, Luis Martin, Zhou, Xin, Wen, Yonggang, Aspuru-Guzik, Alan, Sargent, Edward H., Seh, Zhi Wei
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances at the levels of materials, devices, and systems for the efficient harvesting, storage, conversion, and management of renewable energy. Re
Externí odkaz:
http://arxiv.org/abs/2210.10391
Autor:
Johnston, Andrew, author
Publikováno v:
Entrepreneurial Ecosystems in Cities and Regions : Emergence, Evolution, and Future, 2024.
Externí odkaz:
https://doi.org/10.1093/oso/9780192866264.003.0019
Autor:
Woodhouse, Drew, Johnston, Andrew
Publikováno v:
Critical Perspectives on International Business, 2023, Vol. 19, Issue 5, pp. 661-698.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/cpoib-10-2022-0114