Yu Niu

TL;DR: This paper proposes a practical solution for privacy preserving medical record sharing for cloud computing, where the statistical analysis and cryptography are innovatively combined together to provide multiple paradigms of balance between medical data utilization and privacy protection.

TL;DR: The initial evaluation results illustrate the effectiveness of the proposed neural network classifier for automatic cataract detection based on the classification of retinal images which has great potential to improve diagnosis efficiency of the ophthalmologist and reduce the physical and economic burden of the patients and society.

TL;DR: A framework for privacy preserving data sharing with the view of practical application in more comprehensive way is introduced, which focuses on three key problems of privacy protection during data sharing which are privacy definition and detection, privacy protection policy management, privacy preserving health care data sharing.

TL;DR: A privacy preserving framework for medical data sharing with the view of practical application is proposed and specific Chinese free text EMR segmentation, Protected Health Information PHI extraction, and K-anonymity PHI anonymous algorithms are proposed in each component.

TL;DR: The system is used by approximately 100 rural-to-urban pregnant women in Fengtai District, Beijing, and the experience shows the feasibility of an early-step use of knowledge management and m-health technology in high-risk pregnancy care efforts.