標(biāo)題: Titlebook: Data Management and Analytics for Medicine and Healthcare; Third International Edmon Begoli,Fusheng Wang,Gang Luo Conference proceedings 2 [打印本頁] 作者: inroad 時(shí)間: 2025-3-21 17:41
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作者: 女歌星 時(shí)間: 2025-3-21 22:08
https://doi.org/10.1007/978-3-319-67186-4Association Rule Learning; Big Data; Data Analysis; Databases; Genomics; Information management; Mobile Co作者: 柔聲地說 時(shí)間: 2025-3-22 01:41
978-3-319-67185-7Springer International Publishing AG 2017作者: 精美食品 時(shí)間: 2025-3-22 06:49 作者: 繁榮地區(qū) 時(shí)間: 2025-3-22 12:13
https://doi.org/10.1007/978-3-319-08278-3and variety of big data, materialized data integration is often infeasible or too expensive including the costs of bandwidth, storage, maintenance, and management. . (.n-demand .ig Data .ntegration, .istribution, and .rchestration .ystem) provides a novel on-demand integration approach for heterogen作者: Ibd810 時(shí)間: 2025-3-22 15:58 作者: Ibd810 時(shí)間: 2025-3-22 18:36
https://doi.org/10.1007/978-1-4302-1145-7merging large number of individual Genome-Wide Associations Studies (GWAS) data. Although the emerging of big data platforms such as Hadoop and Spark shed lights on this problem, the inefficiency of keeping data in total-sorted order as well as the workload imbalance problem limit their performance.作者: 準(zhǔn)則 時(shí)間: 2025-3-22 21:21 作者: 我悲傷 時(shí)間: 2025-3-23 04:39 作者: BLA 時(shí)間: 2025-3-23 07:24 作者: 橫條 時(shí)間: 2025-3-23 09:47 作者: 從屬 時(shí)間: 2025-3-23 13:55
Jeffrey Svajlenko,Chanchal K. Royon systems to facilitate the storage and access to patient data, many records are still in paper. Even when data is stored electronically, systems often are complex to use and do not provide means to gather statistical information about a population of patients, thus limiting the usefulness of the d作者: Orchiectomy 時(shí)間: 2025-3-23 21:25
Savo G. Glisic,Pentti A. Lepp?nenves make it possible to access statewide patient data at individual level, such as New York State SPARCS data. The goal of this study is to explore frequent disease co-occurrence and sequence patterns of cancer patients in New York State using SPARCS data. Our collection includes 18,208,830 discharg作者: refine 時(shí)間: 2025-3-24 01:44 作者: headway 時(shí)間: 2025-3-24 04:20
Data Management and Analytics for Medicine and Healthcare978-3-319-67186-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: intelligible 時(shí)間: 2025-3-24 07:21
How Blockchain Could Empower eHealth: An Application for Radiation Oncologyckchain provides a shared, immutable and transparent history of all the transactions to build applications with trust, accountability and transparency. This provides a unique opportunity to develop a secure and trustable EMR data management and sharing system using blockchain. In this paper, we disc作者: epidermis 時(shí)間: 2025-3-24 10:48
On-Demand Service-Based Big Data Integration: Optimized for Research Collaborationand variety of big data, materialized data integration is often infeasible or too expensive including the costs of bandwidth, storage, maintenance, and management. . (.n-demand .ig Data .ntegration, .istribution, and .rchestration .ystem) provides a novel on-demand integration approach for heterogen作者: Alcove 時(shí)間: 2025-3-24 15:46
, – A Service for Collecting, Organizing, Processing, and Sharing Medical Image Data in the Cloudful APIs, and distributed computing allows for complex systems to be realized that address the needs of modern compute intense environments. In this paper, we present a web-based medical image data and information management software platform called . (.loud .ealthcare .mage .rocessing .ervice). Thi作者: Enzyme 時(shí)間: 2025-3-24 23:01
High Performance Merging of Massive Data from Genome-Wide Association Studiesmerging large number of individual Genome-Wide Associations Studies (GWAS) data. Although the emerging of big data platforms such as Hadoop and Spark shed lights on this problem, the inefficiency of keeping data in total-sorted order as well as the workload imbalance problem limit their performance.作者: 逗留 時(shí)間: 2025-3-25 02:40
An Emerging Role for Polystores in Precision Medicinent and promising field of precision medicine, which focuses on identifying and tailoring appropriate medical treatments for the needs of the individual patients, based on their specific conditions, their medical history, lifestyle, genetic, and other individual factors. As we, and a database communi作者: 責(zé)難 時(shí)間: 2025-3-25 04:08 作者: monologue 時(shí)間: 2025-3-25 10:46
Effects of Varying Sampling Frequency on the Analysis of Continuous ECG Data Streamsiate health status, not for real-time analysis because of technical challenges in real-time processing of such massive data. Data storage is also another challenge in making ICU data useful for retrospective studies. Therefore, it is important to know the minimal sampling frequency requirement to de作者: onlooker 時(shí)間: 2025-3-25 12:35
Detection and Visualization of Variants in Typical Medical Treatment Sequencese medical processes by the secondary use of these records. Medical workers including doctors, nurses, and technicians generally use clinical pathways as their guidelines for typical sequences of medical treatments. The medical workers traditionally generate the clinical pathways themselves based on 作者: 神秘 時(shí)間: 2025-3-25 16:47 作者: Adherent 時(shí)間: 2025-3-25 22:04
Association Rule Learning and Frequent Sequence Mining of Cancer Diagnoses in New York Stateves make it possible to access statewide patient data at individual level, such as New York State SPARCS data. The goal of this study is to explore frequent disease co-occurrence and sequence patterns of cancer patients in New York State using SPARCS data. Our collection includes 18,208,830 discharg作者: Petechiae 時(shí)間: 2025-3-26 03:38
Healthsurance – Mobile App for Standardized Electronic Health Records Database a standard based health application. Standards for semantic interoperability propose the use of archetypes for building a health application. A usual practice followed for storing of EHRs is through graphical user interfaces. Generally, user interface is static corresponding to the underlying medic作者: Aesthete 時(shí)間: 2025-3-26 06:24
0302-9743 r Medicine and Healthcare, DMAH 2017, in Munich, Germany, in September 2017, held in conjunction with the 43rd International Conference on Very Large Data Bases, VLDB 2017.?. The 9 revised full papers presented together with 2 keynote abstracts were carefully reviewed and selected from 16 initial su作者: botany 時(shí)間: 2025-3-26 10:02 作者: 全國性 時(shí)間: 2025-3-26 16:05 作者: Folklore 時(shí)間: 2025-3-26 20:20
https://doi.org/10.1007/978-3-319-08278-3proach of virtual and materialized data integrations. By allocating unique identifiers as pointers to virtually integrated data sets, . supports efficient data sharing among data consumers. We design . as a generic service-based data integration system, and implement and evaluate a prototype for multimodal medical data.作者: Negotiate 時(shí)間: 2025-3-26 21:39
DML: Inserting, Updating, and Deleting Datapresents information in a modern feed-like interface, provides access to a growing library of plugins that process these data, allows for easy data sharing between users and provides powerful 3D visualization and real-time collaboration. Image processing is orchestrated across additional cloud-based resources using containerization technologies.作者: defibrillator 時(shí)間: 2025-3-27 02:51 作者: 易于出錯(cuò) 時(shí)間: 2025-3-27 08:08
On-Demand Service-Based Big Data Integration: Optimized for Research Collaborationproach of virtual and materialized data integrations. By allocating unique identifiers as pointers to virtually integrated data sets, . supports efficient data sharing among data consumers. We design . as a generic service-based data integration system, and implement and evaluate a prototype for multimodal medical data.作者: Bronchial-Tubes 時(shí)間: 2025-3-27 10:20 作者: 博愛家 時(shí)間: 2025-3-27 17:35
High Performance Merging of Massive Data from Genome-Wide Association StudiesF files on their Single Nucleotide Polymorphism (SNP) location into a single TPED file. Our methodologies overcame the limitations stated above and considerably improved the performance with good scalability on input size and computing resources.作者: 宮殿般 時(shí)間: 2025-3-27 20:06 作者: 失眠癥 時(shí)間: 2025-3-27 23:26
Savo G. Glisic,Pentti A. Lepp?neniagnosis histories using the cSPADE algorithm. Our data driven approach provides essential knowledge to support the investigation of disease co-occurrence and progression patterns for improving the management of multiple diseases.作者: 令人不快 時(shí)間: 2025-3-28 03:07 作者: 中子 時(shí)間: 2025-3-28 10:12 作者: Guileless 時(shí)間: 2025-3-28 10:58 作者: Lineage 時(shí)間: 2025-3-28 17:52
Conference proceedings 2017 The papers are organized in topical sections on data privacy and trustability for electronic health records; biomedical data management and Integration; online mining of Health related data; and clinical data analytics..作者: 粗糙 時(shí)間: 2025-3-28 21:08
0302-9743 bmissions. The papers are organized in topical sections on data privacy and trustability for electronic health records; biomedical data management and Integration; online mining of Health related data; and clinical data analytics..978-3-319-67185-7978-3-319-67186-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Exhilarate 時(shí)間: 2025-3-29 00:11 作者: 健談 時(shí)間: 2025-3-29 06:53 作者: 哀求 時(shí)間: 2025-3-29 08:32 作者: 親屬 時(shí)間: 2025-3-29 13:47
Detection and Visualization of Variants in Typical Medical Treatment Sequencesl patterns with treatment time information from EMR logs. These patterns tend to contain variants that are influential in verification and modification. In this paper, we propose an approach for detecting the variants in frequent sequential patterns of medical orders while considering time informati作者: 抵押貸款 時(shí)間: 2025-3-29 18:04
