With the development of electronic information technology, electronic medical records (EMRs) have been a common way to store the patients' data in hospitals. They are stored in different hospitals' databases, even for the same patient. Therefore, it is difficult to construct a summarized EMR for one patient from multiple hospital databases due to the security and privacy concerns. Meanwhile, current EMRs systems lack a standard data management and sharing policy, making it difficult for pharmaceutical scientists to develop precise medicines based on data obtained under different policies. To solve the above problems, we proposed a blockchain-based information management system, MedBlock, to handle patients' information. In this scheme, the distributed ledger of MedBlock allows the efficient EMRs access and EMRs retrieval. The improved consensus mechanism achieves consensus of EMRs without large energy consumption and network congestion. In addition, MedBlock also exhibits high information security combining the customized access control protocols and symmetric cryptography. MedBlock can play an important role in the sensitive medical information sharing.
This study measures the effectiveness of combining group discussions, pre-questionings, or both with scaffolding teaching strategies in translation lessons based on Angelelli's translation competence model. However, in practice, the feasibility of using the Angelelli’s scoring scale to measure translation competence requires further verification by other empirical studies. The results of this study are only for reference, in hope that future researchers may contribute to the improvement in this subject.
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