4 citations · 7 across the 4 of their papers we have counts for
4 papers
The Beauty or the Beast: Which Aspect of Synthetic Medical Images Deserves Our Focus?
Xiaodan Xing, Yang Nan, Federico Felder +2
Training medical AI algorithms requires large volumes of accurately labeled datasets, which are difficult to obtain in the real world. Synthetic images generated from deep generati…
Non-Imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Survey
Xiaodan Xing, Huanjun Wu, Lichao Wang +5
Data quality is the key factor for the development of trustworthy AI in healthcare. A large volume of curated datasets with controlled confounding factors can help improve the accu…
Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation
Yang Nan, Javier Del Ser, Zeyu Tang +7
Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming a…
Data Harmonisation for Information Fusion in Digital Healthcare: A State-of-the-Art Systematic Review, Meta-Analysis and Future Research Directions
Yang Nan, Javier Del Ser, Simon Walsh +23
Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features…