nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
AlphaML: A clear, legible, explainable, transparent, and elucidative binary classification platform for tabular data
|
Nasimian, Ahmad |
|
|
5 |
1 |
p. |
artikel |
2 |
An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals
|
Pan, Weishen |
|
|
5 |
1 |
p. |
artikel |
3 |
DSM: Deep sequential model for complete neuronal morphology representation and feature extraction
|
Xiong, Feng |
|
|
5 |
1 |
p. |
artikel |
4 |
Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT
|
Yang, Jingye |
|
|
5 |
1 |
p. |
artikel |
5 |
FHBF: Federated hybrid boosted forests with dropout rates for supervised learning tasks across highly imbalanced clinical datasets
|
Pezoulas, Vasileios C. |
|
|
5 |
1 |
p. |
artikel |
6 |
Functional microRNA-targeting drug discovery by graph-based deep learning
|
Keshavarzi Arshadi, Arash |
|
|
5 |
1 |
p. |
artikel |
7 |
LATTE: Label-efficient incident phenotyping from longitudinal electronic health records
|
Wen, Jun |
|
|
5 |
1 |
p. |
artikel |
8 |
Looking forward to the new year
|
Hufton, Andrew L. |
|
|
5 |
1 |
p. |
artikel |
9 |
Meet the authors: Hanchuan Peng, Peng Xie, and Feng Xiong
|
Peng, Hanchuan |
|
|
5 |
1 |
p. |
artikel |
10 |
Shifting your research from X to Mastodon? Here’s what you need to know
|
Roscam Abbing, Roel |
|
|
5 |
1 |
p. |
artikel |
11 |
Unified fair federated learning for digital healthcare
|
Zhang, Fengda |
|
|
5 |
1 |
p. |
artikel |