output
20192022
most citedStageNet: Stage-Aware Neural Networks for Health Risk Prediction

79 citations

5 papers

physics.med-ph202213 cited

Bone tumor suppression in rabbits by hyperthermia below the clinical safety limit using aligned magnetic bone cement

Xiang Yu, Shan Gao, Dian Wu +12

Demonstrating highly efficient alternating current (AC) magnetic field heating of nanoparticles in physiological environments under clinically safe field parameters has remained a…

eess.IV202123 cited

CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation

Xinru Zhang, Chenghao Liu, Ni Ou +5

Brain lesion segmentation provides a valuable tool for clinical diagnosis, and convolutional neural networks (CNNs) have achieved unprecedented success in the task. Data augmentati…

q-bio.PE20211 cited

Model-based cellular kinetic analysis of SARS-CoV-2 infection: different immune response modes and treatment strategies

Zhengqing Zhou, Zhiheng Zhao, Shuyu Shi +10

Increasing number in global COVID-19 cases demands for mathematical model to analyze the interaction between the virus dynamics and the response of innate and adaptive immunity. He…

cs.LG202079 cited

StageNet: Stage-Aware Neural Networks for Health Risk Prediction

Junyi Gao, Cao Xiao, Yasha Wang +3

Deep learning has demonstrated success in health risk prediction especially for patients with chronic and progressing conditions. Most existing works focus on learning disease Netw…

cs.CV201911 cited

Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model

Wenhui Cui, Yanlin Liu, Yuxing Li +6

Automated brain lesion segmentation provides valuable information for the analysis and intervention of patients. In particular, methods based on convolutional neural networks (CNNs…