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20172023
most citedGenerative AI for Medical Imaging: extending the MONAI Framework

41 citations · 148 across the 22 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.AI2023★ 1 cited

Neuro-Symbolic Recommendation Model based on Logic Query

Maonian Wu, Bang Chen, Shaojun Zhu +3

A recommendation system assists users in finding items that are relevant to them. Existing recommendation models are primarily based on predicting relationships between users and i…

cs.LG2023

Imputing Brain Measurements Across Data Sets via Graph Neural Networks

Yixin Wang, Wei Peng, Susan F. Tapert +2

Publicly available data sets of structural MRIs might not contain specific measurements of brain Regions of Interests (ROIs) that are important for training machine learning models…

eess.IV2023★ 41 cited

Generative AI for Medical Imaging: extending the MONAI Framework

Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot +21

Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to he…

cs.AI2023

Neural-Symbolic Recommendation with Graph-Enhanced Information

Bang Chen, Wei Peng, Maonian Wu +2

The recommendation system is not only a problem of inductive statistics from data but also a cognitive task that requires reasoning ability. The most advanced graph neural networks…

cs.LG2023

Generation of 3D Molecules in Pockets via Language Model

Wei Feng, Lvwei Wang, Zaiyun Lin +9

Generative models for molecules based on sequential line notation (e.g. SMILES) or graph representation have attracted an increasing interest in the field of structure-based drug d…

cs.CL2023

Learning Homographic Disambiguation Representation for Neural Machine Translation

Weixuan Wang, Wei Peng, Qun Liu

Homographs, words with the same spelling but different meanings, remain challenging in Neural Machine Translation (NMT). While recent works leverage various word embedding approach…