The Experts below are selected from a list of 183 Experts worldwide ranked by ideXlab platform
Kenji Araki - One of the best experts on this subject based on the ideXlab platform.
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Performance Assessment of EMR Systems Based on Post-Relational Database
Journal of medical systems, 2011Co-Authors: Xiao-guang Zhang, Yu Tian, Muneou Suzuki, Kenji ArakiAbstract:Post-relational Databases provide high performance and are currently widely used in American hospitals. As few hospital information systems (HIS) in either China or Japan are based on post-relational Databases, here we introduce a new-generation electronic medical records (EMR) system called Hygeia, which was developed with the post-relational Database Cache and the latest platform Ensemble. Utilizing the benefits of a post-relational Database, Hygeia is equipped with an "integration" feature that allows all the system users to access data--with a fast response time--anywhere and at anytime. Performance tests of Databases in EMR systems were implemented in both China and Japan. First, a comparison test was conducted between a post-relational Database, Cache, and a relational Database, Oracle, embedded in the EMR systems of a medium-sized first-class hospital in China. Second, a user terminal test was done on the EMR system Izanami, which is based on the identical Database Cache and operates efficiently at the Miyazaki University Hospital in Japan. The results proved that the post-relational Database Cache works faster than the relational Database Oracle and showed perfect performance in the real-time EMR system.
Yihua Huang - One of the best experts on this subject based on the ideXlab platform.
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ICDE - BENU: Distributed Subgraph Enumeration with Backtracking-Based Framework
2019 IEEE 35th International Conference on Data Engineering (ICDE), 2019Co-Authors: Zhaokang Wang, Chunfeng Yuan, Yihua HuangAbstract:Given a small pattern graph and a large data graph, the task of subgraph enumeration is to find all the subgraphs of the data graph that are isomorphic to the pattern graph. The state-of-the-art distributed algorithms like SEED and CBF turn subgraph enumeration into a distributed multi-way join problem. They are inefficient in communication as they have to shuffle partial matching results that are much larger than the data graph itself during the join. They also spend non-trivial costs on constructing indexes for data graphs. Different from those join-based algorithms, we develop a new backtracking-based framework BENU for distributed subgraph enumeration. BENU divides a subgraph enumeration task into a group of local search tasks that can be executed in parallel. Each local search task follows a backtracking-based execution plan to enumerate subgraphs. The data graph is stored in a distributed Database and is queried as needed. BENU only queries the necessary edges of the data graph and avoids shuffling partial matching results. We also develop an efficient implementation for BENU. We set up an in-memory Database Cache on each machine. Taking advantage of the inter-task and intra-task locality, the Cache significantly reduces the communication cost with controllable memory usage. We conduct extensive experiments to evaluate the performance of BENU. The results show that BENU is scalable and outperforms the state-of-the-art methods by up to an order of magnitude.
Xiao-guang Zhang - One of the best experts on this subject based on the ideXlab platform.
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Performance Assessment of EMR Systems Based on Post-Relational Database
Journal of medical systems, 2011Co-Authors: Xiao-guang Zhang, Yu Tian, Muneou Suzuki, Kenji ArakiAbstract:Post-relational Databases provide high performance and are currently widely used in American hospitals. As few hospital information systems (HIS) in either China or Japan are based on post-relational Databases, here we introduce a new-generation electronic medical records (EMR) system called Hygeia, which was developed with the post-relational Database Cache and the latest platform Ensemble. Utilizing the benefits of a post-relational Database, Hygeia is equipped with an "integration" feature that allows all the system users to access data--with a fast response time--anywhere and at anytime. Performance tests of Databases in EMR systems were implemented in both China and Japan. First, a comparison test was conducted between a post-relational Database, Cache, and a relational Database, Oracle, embedded in the EMR systems of a medium-sized first-class hospital in China. Second, a user terminal test was done on the EMR system Izanami, which is based on the identical Database Cache and operates efficiently at the Miyazaki University Hospital in Japan. The results proved that the post-relational Database Cache works faster than the relational Database Oracle and showed perfect performance in the real-time EMR system.
Lawrence M. Fagan - One of the best experts on this subject based on the ideXlab platform.
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ScroungeMaster: Mobile, Pen-Based Access to Laboratory Information in the Surgical Intensive Care Unit
1996Co-Authors: Jay J. Strain, Ramon Felciano, Adam Seiver, Richard Acuff, Lawrence M. FaganAbstract:Abstract ScroungeMaster provides an alternative to conventional access to laboratory information. A mobile, pen-based system with connection to at Stanford University Medical Center's (SUMC) main laboratory computer, the program retrieves selected patient lab data and stores them in a local Database Cache. Optimized for displaying information by physiologic system, the software uses a context-sensitive display algorithm to determine how lab information is presented. The goal of the project is to decrease access time and increase readability of lab information for the surgical resident.
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Optimizing physician access to surgical intensive care unit laboratory information through mobile computing.
Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium, 1996Co-Authors: Jay J. Strain, Ramon Felciano, Adam Seiver, Richard Acuff, Lawrence M. FaganAbstract:Approximately 30 minutes of computer access time are required by surgical residents at Stanford University Medical Center (SUMC) to examine the lab values of all patients on a surgical intensive care unit (ICU) service, a task that must be performed several times a day. To reduce the time accessing this information and simultaneously increase the readability and currency of the data, we have created a mobile, pen-based user interface and software system that delivers lab results to surgeons in the ICU. The ScroungeMaster system, loaded on a portable tablet computer, retrieves lab results for a subset of patients from the central laboratory computer and stores them in a local Database Cache. The Cache can be updated on command; this update takes approximately 2.7 minutes for all ICU patients being followed by the surgeon, and can be performed as a background task while the user continues to access selected lab results. The user interface presents lab results according to physiologic system. Which labs are displayed first is governed by a layout selection algorithm based on previous accesses to the patient's lab information, physician preferences, and the nature of the patient's medical condition. Initial evaluation of the system has shown that physicians prefer the ScroungeMaster interface to that of existing systems at SUMC and are satisfied with the system's performance. We discuss the evolution of ScroungeMaster and make observations on changes to physician work flow with the presence of mobile, pen-based computing in the ICU.
Zhaokang Wang - One of the best experts on this subject based on the ideXlab platform.
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Distributed Subgraph Enumeration via Backtracking-based Framework.
arXiv: Distributed Parallel and Cluster Computing, 2020Co-Authors: Zhaokang Wang, Yuan Chunfeng, Huang YihuaAbstract:Finding or monitoring subgraph instances that are isomorphic to a given pattern graph in a data graph is a fundamental query operation in many graph analytic applications, such as network motif mining and fraud detection. The state-of-the-art distributed methods are inefficient in communication. They have to shuffle partial matching results during the distributed multiway join. The partial matching results may be much larger than the data graph itself. To overcome the drawback, we develop the Batch-BENU framework (B-BENU) for distributed subgraph enumeration. B-BENU executes a group of local search tasks in parallel. Each task enumerates subgraphs around a vertex in the data graph, guided by a backtracking-based execution plan. B-BENU does not shuffle any partial matching result. Instead, it stores the data graph in a distributed Database. Each task queries adjacency sets of the data graph on demand. To support dynamic data graphs, we propose the concept of incremental pattern graphs and turn continuous subgraph enumeration into enumerating incremental pattern graphs at each time step. We develop the Streaming-BENU framework (S-BENU) to enumerate their matches efficiently. We implement B-BENU and S-BENU with the local Database Cache and the task splitting techniques. The extensive experiments show that B-BENU and S-BENU can scale to big data graphs and complex pattern graphs. They outperform the state-of-the-art methods by up to one and two orders of magnitude, respectively.
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ICDE - BENU: Distributed Subgraph Enumeration with Backtracking-Based Framework
2019 IEEE 35th International Conference on Data Engineering (ICDE), 2019Co-Authors: Zhaokang Wang, Chunfeng Yuan, Yihua HuangAbstract:Given a small pattern graph and a large data graph, the task of subgraph enumeration is to find all the subgraphs of the data graph that are isomorphic to the pattern graph. The state-of-the-art distributed algorithms like SEED and CBF turn subgraph enumeration into a distributed multi-way join problem. They are inefficient in communication as they have to shuffle partial matching results that are much larger than the data graph itself during the join. They also spend non-trivial costs on constructing indexes for data graphs. Different from those join-based algorithms, we develop a new backtracking-based framework BENU for distributed subgraph enumeration. BENU divides a subgraph enumeration task into a group of local search tasks that can be executed in parallel. Each local search task follows a backtracking-based execution plan to enumerate subgraphs. The data graph is stored in a distributed Database and is queried as needed. BENU only queries the necessary edges of the data graph and avoids shuffling partial matching results. We also develop an efficient implementation for BENU. We set up an in-memory Database Cache on each machine. Taking advantage of the inter-task and intra-task locality, the Cache significantly reduces the communication cost with controllable memory usage. We conduct extensive experiments to evaluate the performance of BENU. The results show that BENU is scalable and outperforms the state-of-the-art methods by up to an order of magnitude.
