Zobrazeno 1 - 10
of 598
pro vyhledávání: '"Jiajun, Bu"'
Analytics on large-scale graphs have posed significant challenges to computational efficiency and resource requirements. Recently, Graph condensation (GC) has emerged as a solution to address challenges arising from the escalating volume of graph dat
Externí odkaz:
http://arxiv.org/abs/2402.02000
DeepASD: a deep adversarial-regularized graph learning method for ASD diagnosis with multimodal data
Autor:
Wanyi Chen, Jianjun Yang, Zhongquan Sun, Xiang Zhang, Guangyu Tao, Yuan Ding, Jingjun Gu, Jiajun Bu, Haishuai Wang
Publikováno v:
Translational Psychiatry, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Autism Spectrum Disorder (ASD) is a prevalent neurological condition with multiple co-occurring comorbidities that seriously affect mental health. Precisely diagnosis of ASD is crucial to intervention and rehabilitation. A single modality ma
Externí odkaz:
https://doaj.org/article/e9d79605b8c7442f91bea0c4145fe734
Autor:
Lei Wu, Haishuai Wang, Yining Chen, Xiang Zhang, Tianyun Zhang, Ning Shen, Guangyu Tao, Zhongquan Sun, Yuan Ding, Weilin Wang, Jiajun Bu
Publikováno v:
iScience, Vol 26, Iss 11, Pp 108183- (2023)
Summary: Accurate detection of liver lesions from multi-phase contrast-enhanced CT (CECT) scans is a fundamental step for precise liver diagnosis and treatment. However, the analysis of multi-phase contexts is heavily challenged by the misalignment c
Externí odkaz:
https://doaj.org/article/7f76c3f26a6a4db0b8c6ccd25bf70b60
Publikováno v:
Communications of the ACM. Nov2021, Vol. 64 Issue 11, p70-75. 6p. 4 Color Photographs, 5 Diagrams.
Publikováno v:
Mathematics, Vol 11, Iss 5, p 1073 (2023)
Academic knowledge graphs are essential resources and can be beneficial in widespread real-world applications. Most of the existing academic knowledge graphs are far from completion; thus, knowledge graph completion—the task of extending a knowledg
Externí odkaz:
https://doaj.org/article/1e5b7be76f2142df9710a8cdf7a1319e
Publikováno v:
Frontiers in Endocrinology, Vol 11 (2020)
Primary adenoid cystic carcinoma (ACC) of the upper anterior mediastinum mimicking a thyroid tumor has rarely been seen in clinical practice and lacks a standard of care therapy. Here, we report a 47-year old female patient with an ACC originated fro
Externí odkaz:
https://doaj.org/article/ad235000ca254fd88026e1cb4f9cc284
Autor:
Ning Ma, Jiajun Bu, Lixian Lu, Jun Wen, Sheng Zhou, Zhen Zhang, Jingjun Gu, Haifeng Li, Xifeng Yan
Publikováno v:
Neural Networks. 154:270-282
Semi-Supervised Domain Adaptation has been widely studied with various approaches to address domain shift with labeled source-domain data combined with scarcely labeled target-domain data. Model adaptation is becoming promising with a paradigm of sou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82b9419f3b716af3ab4e690479c45788
https://doi.org/10.1016/j.neunet.2022.07.011
https://doi.org/10.1016/j.neunet.2022.07.011
Publikováno v:
SCIENTIA SINICA Informationis.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c431c2d8dd3ab7b445ffd9bba5c8b52a
https://doi.org/10.1360/ssi-2022-0179
https://doi.org/10.1360/ssi-2022-0179
Autor:
Sheng Zhou, Xin Shen, Zhe Liu, Jiajun Bu, Dian Qin, Hui-Fen Dai, Jing-Jun Gu, Zhi-Hua Wang, Lei Wu
Publikováno v:
IEEE Transactions on Medical Imaging. 40:3820-3831
Recent advances have been made in applying convolutional neural networks to achieve more precise prediction results for medical image segmentation problems. However, the success of existing methods has highly relied on huge computational complexity a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9ff38f0715b47ebdd6210555740b283
https://doi.org/10.1109/tmi.2021.3098703
https://doi.org/10.1109/tmi.2021.3098703
Publikováno v:
2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2678e980741186ac44e1f5b8fb0d760e
https://doi.org/10.1109/isaiee57420.2022.00091
https://doi.org/10.1109/isaiee57420.2022.00091