nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
A deep metric learning approach for histopathological image retrieval
|
Yang, Pengshuai |
|
|
179 |
C |
p. 14-25 |
artikel |
2 |
A novel graph attention adversarial network for predicting disease-related associations
|
Zhang, Jinli |
|
|
179 |
C |
p. 81-88 |
artikel |
3 |
Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis
|
Kosaraju, Sai Chandra |
|
|
179 |
C |
p. 3-13 |
artikel |
4 |
Detecting modeling inconsistencies in SNOMED CT using a machine learning technique
|
Agrawal, Ankur |
|
|
179 |
C |
p. 111-118 |
artikel |
5 |
Editorial Board
|
|
|
|
179 |
C |
p. ii |
artikel |
6 |
Encoder-decoder CNN models for automatic tracking of tongue contours in real-time ultrasound data
|
Hamed Mozaffari, M. |
|
|
179 |
C |
p. 26-36 |
artikel |
7 |
GCN-BMP: Investigating graph representation learning for DDI prediction task
|
Chen, Xin |
|
|
179 |
C |
p. 47-54 |
artikel |
8 |
Interpretable machine learning in bioinformatics
|
Cho, Young-Rae |
|
|
179 |
C |
p. 1-2 |
artikel |
9 |
Logic-based analysis of gene expression data predicts association between TNF, TGFB1 and EGF pathways in basal-like breast cancer
|
Jo, Kyuri |
|
|
179 |
C |
p. 89-100 |
artikel |
10 |
Predicting drug-drug interactions using multi-modal deep auto-encoders based network embedding and positive-unlabeled learning
|
Zhang, Yang |
|
|
179 |
C |
p. 37-46 |
artikel |
11 |
SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning
|
Zeng, Min |
|
|
179 |
C |
p. 73-80 |
artikel |
12 |
Supervised mixture of experts models for population health
|
Shou, Xiao |
|
|
179 |
C |
p. 101-110 |
artikel |
13 |
The message passing neural networks for chemical property prediction on SMILES
|
Jo, Jeonghee |
|
|
179 |
C |
p. 65-72 |
artikel |
14 |
TOP: A deep mixture representation learning method for boosting molecular toxicity prediction
|
Peng, Yuzhong |
|
|
179 |
C |
p. 55-64 |
artikel |