Design and Development of a Medical Big Data Processing System Based on Hadoop

Qin, Yao; Tian, Yu; Li, Pengfei; Tian, Lili; Yang, Qian; Li, Jingsong

doi:10.1007/s10916-015-0220-8

Cited by 72 publications

(34 citation statements)

References 37 publications

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“…The data request and data extraction underwent by using FusionInsight HD platform, which based on framework of Hadoop big data mining technology [39, 40, 41]. We retrospectively reviewed the electronic medical records system of all patients who admitted to our hospital from 1 January 2013 to 31 December 2014.…”

Section: Methodsmentioning

confidence: 99%

Target of obstructive sleep apnea syndrome merge lung cancer: based on big data platform

Lü

Xue

et al. 2017

Oncotarget

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Based on our hospital database, the incidence of lung cancer diagnoses was similar in obstructive sleep apnea Syndrome (OSAS) and hospital general population; among individual with a diagnosis of lung cancer, the presence of OSAS was associated with an increased risk for mortality. In the gene expression and network-level information, we revealed significant alterations of molecules related to HIF1 and metabolic pathways in the hypoxic-conditioned lung cancer cells. We also observed that GBE1 and HK2 are downstream of HIF1 pathway important in hypoxia-conditioned lung cancer cell. Furthermore, we used publicly available datasets to validate that the late-stage lung adenocarcinoma patients showed higher expression HK2 and GBE1 than early-stage ones. In terms of prognostic features, a survival analysis revealed that the high GBE1 and HK2 expression group exhibited poorer survival in lung adenocarcinoma patients. By analyzing and integrating multiple datasets, we identify molecular convergence between hypoxia and lung cancer that reflects their clinical profiles and reveals molecular pathways involved in hypoxic-induced lung cancer progression. In conclusion, we show that OSAS severity appears to increase the risk of lung cancer mortality.

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Section: Methodsmentioning

confidence: 99%

Target of obstructive sleep apnea syndrome merge lung cancer: based on big data platform

Lü

Xue

et al. 2017

Oncotarget

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“…Because of the history of the development of healthcare information technologies, clinical data are typically stored in relational databases (Yao et al 2015a ). Therefore, the hierarchical structure was designed to integrate various hospital information systems (such as RIS, HIS and PACS, etc.…”

Section: Performance Management Information System (Pmis)mentioning

confidence: 99%

Effects of the performance management information system in improving performance: an empirical study in Shanghai Ninth People’s Hospital

Cui

et al. 2016

SpringerPlus

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Improving the performance of clinical departments is not only the significant content of the healthcare system reform in China, but also the essential approach to better satisfying the Chinese growing demand for medical services. Performance management is vital and meaningful to public hospitals in China. Several studies are conducted in hospital internal performance management, but almost none of them consider the effects of informational tools. Therefore, we carried out an empirical study on effects of using performance management information system in Shanghai Ninth People’s Hospital. The main feature of the system is that it provides a real-time query platform for users to analyze and dynamically monitor the key performance indexes, timely detect problems and make adjustments. We collected pivotal medical data on 35 clinical departments of this hospital from January 2013 until December 2014, 1 year before and after applying the performance management information system. Comparative analysis was conducted by statistical methods. The results show that the system is beneficial to improve performance scores of clinical departments and lower the proportion of drug expenses, meanwhile, shorten the average hospitalized days and increase the bed turnover rate. That is to say, with the increasing medical services, the quality and efficiency is greatly improved. In a word, application of the performance management information system has a positive effect on improving performance of clinical departments.

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“…Big Data technologies fall into four main categories: high performance computing, data processing, storage, and resource/workflow allocator, like Hadoop/MapReduce [ 37 – 41 ] ( Table 2 ). A high performance computing (HPC) system is usually the backbone framework of a BDA platform, for example, IBM's Watson and Microsoft Big Data solutions [ 42 ].…”

Section: Methodsmentioning

confidence: 99%

Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services

Chrimes

Zamani

2017

Computational and Mathematical Methods in Medicine

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Big data analytics (BDA) is important to reduce healthcare costs. However, there are many challenges of data aggregation, maintenance, integration, translation, analysis, and security/privacy. The study objective to establish an interactive BDA platform with simulated patient data using open-source software technologies was achieved by construction of a platform framework with Hadoop Distributed File System (HDFS) using HBase (key-value NoSQL database). Distributed data structures were generated from benchmarked hospital-specific metadata of nine billion patient records. At optimized iteration, HDFS ingestion of HFiles to HBase store files revealed sustained availability over hundreds of iterations; however, to complete MapReduce to HBase required a week (for 10 TB) and a month for three billion (30 TB) indexed patient records, respectively. Found inconsistencies of MapReduce limited the capacity to generate and replicate data efficiently. Apache Spark and Drill showed high performance with high usability for technical support but poor usability for clinical services. Hospital system based on patient-centric data was challenging in using HBase, whereby not all data profiles were fully integrated with the complex patient-to-hospital relationships. However, we recommend using HBase to achieve secured patient data while querying entire hospital volumes in a simplified clinical event model across clinical services.

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Design and Development of a Medical Big Data Processing System Based on Hadoop

Cited by 72 publications

References 37 publications

Target of obstructive sleep apnea syndrome merge lung cancer: based on big data platform

Target of obstructive sleep apnea syndrome merge lung cancer: based on big data platform

Effects of the performance management information system in improving performance: an empirical study in Shanghai Ninth People’s Hospital

Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services

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