most citedNeuro-Symbolic Learning: Principles and Applications in Ophthalmology

7 citations · 13 across the 6 of their papers we have counts for

collaborators

6 papers

stat.AP2023

A Longitudinal Analysis about the Effect of Air Pollution on Astigmatism for Children and Young Adults

Lin An, Qiuyue Hu, Jieying Guan +8

Purpose: This study aimed to investigate the correlation between air pollution and astigmatism, considering the detrimental effects of air pollution on respiratory, cardiovascular,…

cs.LG2023★ 2 cited

GAME: Generalized deep learning model towards multimodal data integration for early screening of adolescent mental disorders

Zhicheng Du, Chenyao Jiang, Xi Yuan +10

The timely identification of mental disorders in adolescents is a global public health challenge.Single factor is difficult to detect the abnormality due to its complex and subtle…

cond-mat.soft2023

Biocompatible wearable touch panel based on ionically conductive organic hydrogels with anti-freezing, anti-dehydration, self-healing, and underwater adhesion properties

Zhenglin Chen, Jiaqi Yang, Likun Zhang +16

Next-generation touch panels are poised to benefit from the use of stretchable and transparent soft ionic conductors, but these materials face several challenges in practical appli…

q-bio.QM2022★ 1 cited

Current and perspective sensing methods for monkeypox virus: a reemerging zoonosis in its infancy

Ijaz Gul, Changyue Liu, Yuan Xi +12

Objectives The review is dedicated to evaluate the current monkeypox virus (MPXV) detection methods, discuss their pros and cons, and provide recommended solutions to the problems.…

cs.CV2022★ 7 cited

Neuro-Symbolic Learning: Principles and Applications in Ophthalmology

Muhammad Hassan, Haifei Guan, Aikaterini Melliou +24

Neural networks have been rapidly expanding in recent years, with novel strategies and applications. However, challenges such as interpretability, explainability, robustness, safet…

eess.IV2022★ 3 cited

Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference

Yang Liu, Ersi Zhang, Lulu Xu +13

Deep learning techniques have shown great potential in medical image processing, particularly through accurate and reliable image segmentation on magnetic resonance imaging (MRI) s…