Phenotype Algorithm based Big Data Analytics for Cancer Diagnose.
Nowadays, Cancer diagnosis is one of the major challenging characteristics for treating cancer. The reality of cancer patients rely on the diagnosis of cancer at the early stages (either in stage 1 or stage 2). If the cancer is diagnosed in stage 3 or later stages means the changes of survival of th...
| Published in: | Journal of Medical Systems Vol. 43; no. 8 |
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| Main Authors: | , , |
| Format: | algorithm equations & formulas research tables/charts Journal Article |
| Published: |
Springer Nature
Aug2019
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137490065&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137490065 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Aug2019 vid: 43 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137490065 137490065 137490065 10.1007/s10916-019-1409-z 137490065 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Phenotype Algorithm based Big Data Analytics for Cancer Diagnose. aug: au: Sivakumar, K. Nithya, N. S. Revathy, O. affil: Anna University, Chennai, India sug: subj: Data Analytics Neoplasms Diagnosis Phenotype Algorithms Machine Learning Information Storage Methods Artificial Intelligence Electronic Health Records Data Management Methods Chromosome Mapping Disease Attributes Pain Threshold Simulations Information Retrieval Bar Coding Data Mining Conceptual Framework ab: Nowadays, Cancer diagnosis is one of the major challenging characteristics for treating cancer. The reality of cancer patients rely on the diagnosis of cancer at the early stages (either in stage 1 or stage 2). If the cancer is diagnosed in stage 3 or later stages means the changes of survival of the patient will become more critical. Normally, single patient records will generate a huge amount of data if the data could be manage and analyze means to solve many problems for identifying the patterns it will leads to diagnose the cancer. Recent work several machine learning algorithms are introduced for the classification of cancer. However still the classification accuracy of machine learning algorithms are reduced because of huge number of samples. So the proposed work introduces a new Hadoop Distributed File System (HDFS) is focused in this work. In this paper, the proposed phenotype techniques are used which handle and classifies the raw EHR (Electronic Health Record) and EMR (Electronic Medical Record). It is based on the HDFS and Two-Phase Map Reduce. Phenotype algorithm uses NLP (National Language Processing) tool which will analyze and classify the cancer patient data like gene mapping, age related data, image and ultrasonic frequency processing, identification and analysis of irregularities, disease and personal histories. In this paper, the three factorized model is used which calculates the mean score values. The values are calculated by disease stage, pain status, etc. This paper focuses big data analytics for cancer diagnosis and the simulation results shows the proposed system produces the highest performance. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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