Jiajun Bu
Overview
Explore the profile of Jiajun Bu including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
30
Citations
75
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
1.
Zheng Z, Zhou S, Xu H, Gu M, Xu Y, Li A, et al.
Neural Netw
. 2024 Dec;
184:107014.
PMID: 39733698
Graph Neural Networks (GNNs) have achieved remarkable success in various graph mining tasks by aggregating information from neighborhoods for representation learning. The success relies on the homophily assumption that nearby...
2.
Gao Y, Zhang X, Sun Z, Chandak P, Bu J, Wang H
Adv Sci (Weinh)
. 2024 Dec;
:e2404671.
PMID: 39630592
Accurate prediction of Adverse Drug Reactions (ADRs) at the patient level is essential for ensuring patient safety and optimizing healthcare outcomes. Traditional machine learning-based methods primarily focus on predicting potential...
3.
Wang Z, Gu J, Zhou W, He Q, Zhao T, Guo J, et al.
Int J Neural Syst
. 2024 Sep;
35(1):2450068.
PMID: 39343431
With the rapid advancement of deep learning, computer-aided diagnosis and treatment have become crucial in medicine. UNet is a widely used architecture for medical image segmentation, and various methods for...
4.
DeepASD: a deep adversarial-regularized graph learning method for ASD diagnosis with multimodal data
Chen W, Yang J, Sun Z, Zhang X, Tao G, Ding Y, et al.
Transl Psychiatry
. 2024 Sep;
14(1):375.
PMID: 39277595
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...
5.
Liu M, Zhang Z, Ma N, Gu M, Wang H, Zhou S, et al.
Neural Netw
. 2024 May;
177:106396.
PMID: 38805798
Graph Neural Networks (GNNs) have demonstrated remarkable success in graph node classification task. However, their performance heavily relies on the availability of high-quality labeled data, which can be time-consuming and...
6.
Li J, Zhou S, Li L, Wang H, Bu J, Yu Z
Neural Netw
. 2024 May;
177:106386.
PMID: 38776761
In scenarios like privacy protection or large-scale data transmission, data-free knowledge distillation (DFKD) methods are proposed to learn Knowledge Distillation (KD) when data is not accessible. They generate pseudo samples...
7.
Yuan X, Wang H, Sun Z, Zhou C, Chu S, Bu J, et al.
Cell Rep Methods
. 2024 Mar;
4(3):100733.
PMID: 38503288
Here, we present Anchored-fusion, a highly sensitive fusion gene detection tool. It anchors a gene of interest, which often involves driver fusion events, and recovers non-unique matches of short-read sequences...
8.
Wu L, Wang H, Chen Y, Zhang X, Zhang T, Shen N, et al.
iScience
. 2023 Nov;
26(11):108183.
PMID: 38026220
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...
9.
Zhou C, Wang H, Zhou S, Yu Z, Bandara D, Bu J
Neural Netw
. 2023 Sep;
167:615-625.
PMID: 37713767
Recent research efforts on Few-Shot Learning (FSL) have achieved extensive progress. However, the existing efforts primarily focus on the transductive setting of FSL, which is heavily challenged by the limited...
10.
Ma N, Bu J, Lu L, Wen J, Zhou S, Zhang Z, et al.
Neural Netw
. 2022 Aug;
154:270-282.
PMID: 35917664
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...