Design and Implementation of Highly Secure Residents Management System Using Blockchain

This article presents the design and implementation of highly secure and reliable database system for resident records management system using blockchain technology. Blockchain provides highly secure and reliable data access environment. In blockchain, several data fragments are packed into one block and all blocks are connected to form the chain of blocks. In our prototype, each event of resident such as birth, moving, employment and so on, is assigned to data fragment and certain amount of data fragment, says 20 fragments are packed into block. We also developed the web application interface to avoid installing any applications in users’ PC or smartphone. Prototype development proved the possibility to use the blockchain technology to large amount of data management system with highly secure and reliable features.

The Development and Application of Color Doppler Ultrasound Image-text Management System

In this paper, the advantages and disadvantages of the existing ultrasonic image management system are analyzed, and also a multi-functional color Doppler ultrasound image-text management system is researched and developed in combination with the experience of color Doppler ultrasound doctors. With this system, the related operations such as color Doppler ultrasound images acquisition, processing, preservation, and medical records are implemented. In the design of the system, a professional acquisition card is used for implementing the acquisition of ordinary video signals. In the meantime, DICOM interface is designed using DICOM3.0 protocol for implementing multi-mode acquisition.

A survey of automated International Classification of Diseases coding:development,challenges,and applications

The International Classification of Diseases(ICD)is an international standard and tool for epidemiological in-vestigation,health management,and clinical diagnosis with a fundamental role in intelligent medical care.The assignment of ICD codes to health-related documents has become a focus of academic research,and numerous studies have developed the process of ICD coding from manual to automated work.In this survey,we review the developmental history of this task in recent decades in depth,from the rules-based stage,through the traditional machine learning stage,to the neural-network-based stage.Various methods have been introduced to solve this problem by using different techniques,and we report a performance comparison of different methods on the pub-licly available Medical Information Mart for Intensive Care dataset.Next,we summarize four major challenges of this task:(1)the large label space,(2)the unbalanced label distribution,(3)the long text of documents,and(4)the interpretability of coding.Various solutions that have been proposed to solve these problems are analyzed.Further,we discuss the applications of ICD coding,from mortality statistics to payments based on disease-related groups and hospital performance management.In addition,we discuss different ways of considering and evaluat-ing this task,and how it has been transformed into a learnable problem.We also provide details of the commonly used datasets.Overall,this survey aims to provide a reference and possible prospective directions for follow-up research work.