Zobrazeno 1 - 10
of 170
pro vyhledávání: '"Li Li Jia"'
Publikováno v:
Clinical Case Reports, Vol 11, Iss 2, Pp n/a-n/a (2023)
Abstract Left atrial appendage (LAA) is a finger‐like muscular extension of the left atrium, and it is the most prominent site for cardiac thrombus in patients with atrial fibrillation. Congenital absence of LAA could be incidentally detected in pa
Externí odkaz:
https://doaj.org/article/d71bd8759e77405d8680d31122f69b63
Foundation Metrics for Evaluating Effectiveness of Healthcare Conversations Powered by Generative AI
Autor:
Abbasian, Mahyar, Khatibi, Elahe, Azimi, Iman, Oniani, David, Abad, Zahra Shakeri Hossein, Thieme, Alexander, Sriram, Ram, Yang, Zhongqi, Wang, Yanshan, Lin, Bryant, Gevaert, Olivier, Li, Li-Jia, Jain, Ramesh, Rahmani, Amir M.
Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably
Externí odkaz:
http://arxiv.org/abs/2309.12444
Autor:
Haydarov, Kilichbek, Shen, Xiaoqian, Madasu, Avinash, Salem, Mahmoud, Li, Li-Jia, Elsayed, Gamaleldin, Elhoseiny, Mohamed
We introduce Affective Visual Dialog, an emotion explanation and reasoning task as a testbed for research on understanding the formation of emotions in visually grounded conversations. The task involves three skills: (1) Dialog-based Question Answeri
Externí odkaz:
http://arxiv.org/abs/2308.16349
Autor:
Ostmeier, Sophie, Axelrod, Brian, Verhaaren, Benjamin F. J., Christensen, Soren, Mahammedi, Abdelkader, Liu, Yongkai, Pulli, Benjamin, Li, Li-Jia, Zaharchuk, Greg, Heit, Jeremy J.
Publikováno v:
Sci Rep 13, 16153 (2023)
To determine if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to neuroradiologists. Non-contrast CT (NCCT) examinations from 232 acute ischemic stroke patients who w
Externí odkaz:
http://arxiv.org/abs/2211.15341
Autor:
Ostmeier, Sophie, Axelrod, Brian, Bertels, Jeroen, Isensee, Fabian, Lansberg, Maarten G., Christensen, Soren, Albers, Gregory W., Li, Li-Jia, Heit, Jeremy J.
Performance metrics for medical image segmentation models are used to measure the agreement between the reference annotation and the predicted segmentation. Usually, overlap metrics, such as the Dice, are used as a metric to evaluate the performance
Externí odkaz:
http://arxiv.org/abs/2209.13008
Autor:
Feng, Zhanpeng, Zhang, Shiliang, Takezoe, Rinyoichi, Hu, Wenze, Chandraker, Manmohan, Li, Li-Jia, Narayanan, Vijay K., Wang, Xiaoyu
Active learning is an important technology for automated machine learning systems. In contrast to Neural Architecture Search (NAS) which aims at automating neural network architecture design, active learning aims at automating training data selection
Externí odkaz:
http://arxiv.org/abs/2207.13339
Autor:
Huang, Phoenix X., Hu, Wenze, Brendel, William, Chandraker, Manmohan, Li, Li-Jia, Wang, Xiaoyu
This paper introduces an open source platform to support the rapid development of computer vision applications at scale. The platform puts the efficient data development at the center of the machine learning development process, integrates active lea
Externí odkaz:
http://arxiv.org/abs/2111.10046
This paper explores object detection in the small data regime, where only a limited number of annotated bounding boxes are available due to data rarity and annotation expense. This is a common challenge today with machine learning being applied to ma
Externí odkaz:
http://arxiv.org/abs/1910.07169
Autor:
Ostmeier, Sophie, Axelrod, Brian, Isensee, Fabian, Bertels, Jeroen, Mlynash, Michael, Christensen, Soren, Lansberg, Maarten G., Albers, Gregory W., Sheth, Rajen, Verhaaren, Benjamin F.J., Mahammedi, Abdelkader, Li, Li-Jia, Zaharchuk, Greg, Heit, Jeremy J.
Publikováno v:
In Medical Image Analysis December 2023 90
Multi-task learning holds the promise of less data, parameters, and time than training of separate models. We propose a method to automatically search over multi-task architectures while taking resource constraints into consideration. We propose a se
Externí odkaz:
http://arxiv.org/abs/1908.04339