The application also offers the option to book an appointmentwithadoctortodiscusshealth relatedissues andgetathoroughdiagnosis.
1. INTRODUCTION
2. RELATED WORK
Thehealthcareindustryhasgrownsignificantlyoverthepast fewyears.
touseadatamineinhealthcareisvery good, because the healthcare sector is rich in information, anddataminingbecomesanecessity.Theuseofinformation technologyallowsautomateddataextractionprocessesthat facilitate the acquisition of interesting and common information,whichmeansthecompletionofmanualtaskand the easy retrieval of data directly from electronic records, transferred to a secure electronic system of life saving medicalrecordsandreducingthecostofhealthcareservice,
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International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056
Smart Health Prediction System
Abstract This paper aims at the development of a cloud based forecasting app and outlines the components that make up a life prediction system. users can use this cloud based web application anytime they feel uncomfortable in their lives and try to ignore it. They can visit the app and provide details of their problem and other information related to their bodies such as weight and height and based on that our app will provide accurate information related to their health. There is no limit to access resources.
The age of digital technology requires the worldtoprovide the best possible health care system, to ensure that citizens and communities are alive and well. This study suggests the use of a mining health data mining algorithm that could ultimately establish an appropriate patient health prediction system. Although, health care is available to everyone in the world, there is still no system of health care that is completelyreliable and accurate to diagnose a patient carefully in his or her current health issues. Although some hospitals are well equipped to provide the best possible healthcare for their citizens, some hospitals are still lacking in quality. Therefore, patients are sceptical and uncertainwhenit comes tochoosing which hospital is best for them. Ultimately, these problems undermine the ability of hospitals to manage their management and operations more effectively in order to maintain the health of all citizens and communities. Patients need accurate and accurate treatment and diagnosis in order to recover and for their proper health and medical staff need to be well equipped with their clinical knowledge and communication skills to carefully evaluate their patients to ensure good health. Therefore, the use ofdata mining inhealth forecasts is considered in this paper as the best way to help a better health care system.
Volume: 09 Issue: 03 | Mar 2022 www.irjet.net ISSN: 2395 0072 IRJET Factor value: 7.529 9001:2008
1MCA, School of Computer Science & IT, Jain University, Bangalore, India. 2Professor, School of Computer Science & IT, Jain University, Bangalore, India. ***
This process has gained tremendous importance in the medical field. It is estimated that a care hospital can producefiveterabytesofdataperyear.
Key Words: AWS,CloudBased,CSS,Database,Html,Smart HealthPrediction,SmartHealth,JavaScript,MySQL,php
Therefore, in order to overcome the problems that people havewiththeirhealthproblems,wehavedevelopedaneasy to use app that helps users get tested at their place of residenceatanytime
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People's health is one of the most important factors contributingtoeconomicdevelopmentinanyeconomy.The most important and immediate consequences of a global declinetaketheformofdamagetohumanhealth
There is a very nice and attractive web basedcloud basedweb application that is easy to understand and use. The web service is secure and personal. the web app is designed to be easy to use with no hidden feature and the user can easily access this web application. there is a fast and efficient communication between users and the application server.
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Nishant Kumar1, Dr. Bhuvana J2
[1] This paper introduces an update to the use of the AprioriAlgorithmindatasetsusingamachinelearningtool. RuijuanHupresentstheconceptdetailsoftwocommondata stepsusingApriorialgorithmsandOrganizationRules.This speaks to a new development called the Improved Apriori Algorithm to eliminate the evils of the Apriori algorithm. Gitanjali J, et.al proposes the study of large data sets from various angles and the acquisition of a wealth of useful information. These methods are helpful in diagnosing and administering effective treatment. Krishnaiahet.al. aims to addressavarietyofdataminingmethodsindecision making processesandprovideadetailedtreatmentdiscussion.Data miningtechniquescanimproveclinicalguessingangles.Dan A. Simovici suggested that organizational rules represent informationindatasetsasaresultandisdirectlyrelatedto thecalculationofcommonsetsofobjects.Md.AbdulKhalel argues that data mining as a concept that reads large amountsofdataandextractspatternscanbetranslatedinto useful
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[2]informationThetendency
[4]Thispaperprovidesananalysisofvariousdatamining procedures that can help medical analysts or physicians diagnoseaccurateheartdisease.Themainmethodusedin ourworkwaspublishedinresearch,journalsandreviewsin thefieldsofcomputerscienceandengineering,datamining andheartdiseaseinrecenttimes
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that health facilities are able to processdataminingapplicationsinavarietyofareas,suchas nurses using patterns by measuring clinical indicators, quality indicators, customer satisfaction and economic indicators, practicing physicians in many developmental perspectives. resource utilization, cost effectiveness and evidence based decision making, identifying high risk patientsandearlyintervention,improvinghealthcare,etc
[5]sets.Nowadays
as well as the early detection of communicable disease throughimproveddatacollections.Dataminingcanenable health care organizations to predict patient styles and behaviors, which are achieved by analyzing data from different perspectives and gaining connections and relationshipsfromseeminglylogicalinformation.Rawdata fromhealthcareorganizationisplentifulandvaried.They needtobecollectedandstoredinanorganizedmanner,and their integration enables them to focus on the hospital information system. Smart Healthcare data mining offers manyopportunitiesforhiddenpatterninvestigationsfrom thesedatasets.Thesepatternscanbeusedbyphysiciansto determinethediagnosisandtreatmentofpatientsinhealth care
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[6]AsoneofthekeystrategiesinPrognosticsandHealth Management(PHM),thepredictablyaccurateSurvivalLiving Life(RUL)caneffectivelyreducetheamountofleisuretime andsignificantlyimprove economicbenefits.Inthispaper, the standard RUL method of forecasting is proposed for complexsystemswithmultipleConditionMonitoring(CM) indicators.Thestockcorruptionmodelisproposedtoreflects system damaging behavior, based on where consecutive reliability factors such asRUL and ConfidenceInterval are clearlyidentifyit.Consideringthedestructivemodel,thetwo most desirable areas of Health Indicator (HI) have been prioritized and their value assessment methods are being developed. With the required structures, an indirect data aggregationmethodbasedonGeneticProgramming(GP)is proposedtocreateamorecohesiveHIcombination.Inthis way,morecommon modesignalsareintegratedtoprovide better guessing power. Finally, the proposed integrated
Data mining provide a link between continuous data information, such as biomedical signals collected from patients in emergency care centers, and creates a smart monitoring system that sends pre selected reminders, warnings, and alarms to emergencies. Applying organizationalrulesinvolvesfindingalltherules,oratleast partofthebasicprinciplesthatmarkcertaininformationasa resultorasaprecursor.Thistypeofproblemisofparticular interest to health professionals who are looking for a relationshipbetweendiseaseandlifestyleorpopulationor betweensurvivalandtreatmentrates
This paper aims to analyze the various data mining methodsintroducedinrecentyearstopredictheartdisease. The notes show that Neural networks with 15 attributes work much better than all other data mining techniques, anotherconclusionfromtheanalysesisthatthedecisiontree also showed good accuracy with the help of a genetic algorithmandasmallsetselection.Thetendencytoinclude data mininginsmarthealthcareisverygood,becausethe healthcare sector is rich in information, and data mining becomesanecessity.Healthcareorganizationsproduceand collect large quantities of information daily. The use of information technology allows automated data extraction processes that help to obtain enjoyable information and regulartimes,whichmeansthecompletionofmanualtasks
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International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056
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Heartdiseaseistheleadingcauseofdeath today.Thetreatmentofpatientswithheartdiseasehasbeen improved, for example with mechanical mobility (M2M) technologysothatwecanmonitorthepatientremotely.In ordertouseM2Mtocareforadistantheartpatient,hisor hermedicalconditionmustbeadjustedfromtimetotimeat home.Therefore,it'sdifficulttoperformcomplexteststhat requiredoctorstohelp.Inthemeantime,heartdiseasecanbe predicted by analyzing some of the patient's health principles. With the help of data mining procedure, the prognosisforheartdiseasecanbeimproved.Therearesome algorithms which is used for this purpose such as Naive Bayes, Decision Tree, and k Nearest Neighbor. This study aims to use data mining techniques for predicting heart disease,withsimplificationparametertobeused,forusein M2Mforthepurposeofmonitoringremotepatient.KNNis usedasa parameter measure to improveaccuracy. Only8 parameters(13recommendedparameters)areusedasthey arethesimplestandfastestparametersthatcanbemeasured athome.Theresultshowsthattheaccuracyoftheseeight parameters using the KNN algorithm is good enough, compared to the 13 parameters per KNN, or even other algorithmssuchasNaivebayes.
[3]organizations.Thepaperstates
andtheeasyremovalofdatadirectlyfromelectronicrecords, transferredtoasecureelectronicsystemforfuturemedical record.healthandreducethecostofhealthcareservices,as wellastheearlydetectionofcommunicablediseasesthrough improveddatacollection.Dataminingcanenablehealthcare organizations to predict patient tendencies and behaviors, which are achieved by analyzing data from different perspectivesandgainingconnectionsandrelationshipsfrom seeminglydesignedinfo1mation.Rawdatafromsmarthealth care organizations is plentiful andvaried. They need tobe collected and stored in an organized data, and their integrationenablesthemtofocusonthehospitalinformation system. Smart Healthcare data mining offers many opportunitiesforhiddenpatterninvestigationsfromthese data
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3. ANALYSIS AND INTERPRETATION
From this application the user can easily see the problem theyareexperiencingandtheexcitingpartisthattheuser canfinditanywhereandanytime,itwillnottakemuchtime andtheuserdoesnothavetogoonlineorwaitlong.tofind timeandconsultadoctor.
Todaypeopleareverybusywiththeirhealthanddonotcare abouttheirhealth,theyonlytakeactionwhenitisasensitive issueanditisbecausetheydonothavemuchtimeordonot want to spend much time in the area. a place where they found Peoplenothing.thinknot
Fig:1 A working model
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System Simulation
UsingHTML,cascade,andjavascriptIcreatedmyinteractive interaction.andwecanusetheloopingfeatureinHTMLdu thatwecanuse a small longslidecodeorany module we havetorepeat.MySQLprovidesdatastorageonawebsite.
Thefinaluserflowofmymodelcoveri.e.,user/customer. The Customer / User can visit the app and can fill in the requiredinformationbasedonamattertheysimplyignore orwanttocheckanduserdatawillbeanalyzedthroughour databaseandbasedonthegameapplicationwillprovidea reportandadoctor.detailsifthereisamajorproblemwith theirhealth.
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for
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approach is validated in Commercial Modular Aero Propulsion data set aircraft turbine conservationcolonysystemstorage,technologiesstoragestructuresthiscapacitymodediscussesstorage(Kmicroarray641patientsgenes.ReferenceCloudservices,Computingcloudinfrastructure.Thesereliability,cloudinfrastructurecomputing,efficientCloudCloudvipreventingandassessnonindividualprioritized:preventionknowledgepublicbasiseffectivenessareevaluatioidentification,strategies:publichealthmonitoring,riskgroupriskassessment,andimplementation/nprogram.Theabilitytopredictwhichindividualsathighriskofinjury(orproduceinjury)andthelimitedandcostofotherpreventionstrategiesisthefordecisionsthataffecttheenvironmentandfocusonhealthpreventionstrategies.Inordertobuildabaseonwhichtobasedecisionsonviolencestrategies,thefollowingactivitiesshouldbe(a)developingsurveillanceprogramsrelatedtoviolence;(b)specificallyidentifygroupsatriskoflethalviolence;(c)usecasemanagementtechniquestopotentialriskfactorsforinjuryandviolentbehavior;(d)acarefulreviewofexistingprogramsaimedatpublicviolenceoralteringthethreatoftheolence.[8]Asanemergingtechnologyandbusinessparadigm,Computinghastakencommercialcomputingbystorm.computingprovideseasyaccesstothecompany'smoststorageinfrastructureforwebservices.WithcloudthegoalistohidethecomplexityofITmanagementforitsusers.Atthesametime,computingplatformsofferhighoutput,99.999%highperformance,andaccurateconfiguration.skillsareofferedatalowcostcomparedtodedicatedThisarticleprovidesaquickintroductiontostorage.ItintegrateskeytechnologiesinCloudandCloudStorage,afewdifferenttypesofcloudandexplainstheadvantagesanddisadvantagesofStoragefollowingthelaunchoftheCloudStoragemodel.[9]PengZ,Examinedgeneticembryonicstemcell(ESC)signaturesvaluetoestimatesurvivalProstatecanceratthetimeoftheirdiagnosis.Kuresearch,atotalofESCgenepredictors(ESCGPs)identifiedusingdatasets.MeasurementsurvivalneighbornearkNN)usinganalgorithmestimatingtotalsurvival[84].[10]Thispaperproposesacommondesignofthecloudsystem,analyzescomponentfunctions,andkeytechnologies,etc.Cloudstorageisanovelofnovelstorageserviceprovidersthatprovidestorageandonlinedatastorageservicestocustomers;Attime,clientsdonotneedtoknowthedetailsandwithdiscountsandmethods.Theproposedcloudstructureishorizontalandintegrated,andthemaindiscussedinvolveutilization,virtualizationofdataediting,migration,security,etc.Anoperatingthatincludesnaturalsequencing,gametheory,antdevelopment,datalifecyclemanagement.,andregeneration,integrationandevolutionary
processesarealsoanalyzed.So,acompleteandinnovative viewofthecloudstoragesystemispresented.
Thiswebapplicationsavestimeandmoneyforusers.They do not need to spend thousands of rupees on hospitals if theyhaveaminorproblem.
Inourpaper,herewehavemadeacloud basedapplication for a more effective way to tackle the health care system. Cloudgivesusaflexiblefeature,usingacomputercloudis essentialinhelpingbusinessesandindividualsrealizeand fulfillthepromiseofdigitalchange.
Research Journal of Engineering and
engines.[7]Timely
onlyoftheirfinancialsituationbutalsoof howtheycangrowitdayinanddayoutbutbythinkingthat theyalsoignoretheproblemtheyfaceineverydaylifeand simplyignoreitfornoapparentreason.
My model data will flow into the first three phase phase, which is the login or registration phase where usage can register or login. After that is the forum where users can selectthereleasedetails.Afterthatitcomesoutwhereusers canbesafefromunauthorizedusers.
Therearevariousdataminingtechniquestochoosefromto turnrawdataintouseful.Theseareseventechniquesthat are most commonly used involved data mining to choose fromfig3
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InformationrepresentationisthelaststepforKDDwhere visualization tools and techniques are used to help users understandinformationfromthedataminingresult
Pattern Examination is defined as the identification of patterns that represent information based on a particular scale.
Fig:3
4.1 Data Mining
Data aggregation is the second step after Data Cleaning which takes the filtered data from a previous step to be mergedintousefulandusefuldata.
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Datamininginvolvesexaminingthedataofanypatternsor rulesthatareusefulforextractingandretrieving
4.1.3 Data Selection
Data Selection is defined as the process by which data relevanttoanalysisisselectedanddownloadedfromdata collection.
4.1.4 Data Transformation
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Both K. Durairaj and H. Ranjani which is shown in fig 4.1, mentionedthattheresultofdataminingareofinfluenceof statistics,database,informationretrieval,machinelearning and Dataalgorithms.miningisalso
International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056
Knowledge representation
Thissectiondescribesdataminingprocessesandalgorithms fortheireffectivenessinhealthassumptions.Italsoanalyzes prospects related to the use of data mining techniques in healthforecasts.
4.1.1 Data Cleaning
Data Transformation involves the conversion of data into formsneededtoperformvariousminingoperationssuchas smoothing,orientingormerging.
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Data Cleaning is presented as the first step for KDD to eliminateanyrandom,insignificantormissingvaluedata.
awell knownprocessthatinvolvesthe AcquisitionofInformationonaSitewhichistheextraction oflargeamountsofdatafromawebsite.It isusedtowork andexplorehiddenpatternandrelationshipthatcouldbe found in large amounts of data for decision making purposes. Knowledge Discovery in Database is done in 7 sequentialstepsasshowninFigure[2]
4.1.6 Pattern Evaluation
4. IMPLEMENTATION
4.1.5 Data Mining
4.1.2 Data Integration
Fig:2 Historical Perspective of Data Mining
Theforecastingsystemwilldependonitsuseofdatamining, called mining information and information from a large numberofdatasets.Themedicalindustryisoneofthemany fieldsinthecommunitythatcollectalotofinformationthat can be used to help with data mining. Data mining can improvethemedicalindustriesbyeliminatingcurrenthealth disparitiesbyeasilyprovidinganswertocomplexmedical conditioninordertoresolveandeliminateanytimewasted inmakingaclinicaldecision
4.1.7
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Data mining is defined as the process of searching for specific patterns that come to a website and using that information to create speculative models. Its processes include analyzing and selecting specific data in a large databasetorevealnewandunknownpatterns
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The resultoftheproposed system will bediseaseand the levelofaccuracywithwhichthepatientiscurrentlybeing treated.Asthedataareanalyzedbyfollowingthestepsof the Information Access process based on Figure 1.1, the accuracy level of a particular disease will be based on a varietyoffactorssuchasthepatient'smedicalhistory,age, genderandmuchmore.Thefollowingdataminingresultwill be used toassistclinical physiciansto be able totreat the patientdependingonthediseaseswithhighaccuracy
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4.4 Regression
4.7 Prediction
A sequential pattern is a method that focuses on finding similarpatternsindataactivityovertime.Thisapplicationis usefulforrevealingperiodicdatadeviations.
4.3 Clustering
Theimplementationofahealthforecastingsystemwillallow physiciansandmedicalprofessionalstolimittheireffortsin their clinical decision making process by simply inserting user health data and symptoms. This system will be used withdataminingalgorithmsthatcanintelligentlydiagnose the disease by linking patient information with health informationprovidedbydoctorsandmedicalprofessionals and stored on a website, the whole process will be successful. reducing the time consuming and challenging effortsthatphysiciansputintoittomakeaclinicaldecision. Theprogramwillalsoencouragepatientsandcliniciansto consultonapatientrecommendationforphysicianswhoare qualified to deal with their diagnosis and who are not importantintheirparticularmedicalfield.
International Research Journal of Engineering and Technology (IRJET) e ISSN: 2395 0056
© 2022, IRJET | Impact Factor value:
It is a method used in data modeling features. The relationship betweenthetwomayvaryaccording totheir circumstances
Predicting merely means analyzing past events to make predictions.Therefore,thehistoricaldataisusedfortesting to gain insight that may be helpful in predicting future events
Volume: 09 Issue: 03 | Mar 2022 www.irjet.net
Fig:4
4.8 Association Rules
Thisprojectaimstobringaneasy to useplanforpatients andphysicianstoapplytheirneedstodiagnoseillnessand provideappropriateguidanceontheircurrenthealthissue. ThesoftwareitselfwillonlyfitandbeinstalledonPCsorcan be deployed over cloud so that it could accessed from anywhere
Organizational rules are a statistical related data mining program.Searchesanddisplaysspecificconnectiondatathat canbelinkedbetweentwopre setdatatodetectahidden Withpattern.thehealthcareforecastingsystem,thereareanumber of data mining algorithms to consider. Every data mining algorithmwilleventuallyproducedifferentresultsbetween eachotherandwiththeseresults,itisusedtodeterminethe efficiencyandaccuracyofthesystem.Thestudyproposedby Kirubha and Manju Priya which is shown in figure 4, describes an analysis of the application of data mining in differentmedicaldomainandthealgorithmthatareusedto predict different diseases. A table in Figure 4 shows the comparisonofalgorithmthatwereusedfordifferentdisease prediction.WiththeresultshowninFigure4,itissufficient to determine that data mining provides results that are betterandusefulinprovidingdiagnosisfordiseasewhenthe correctdataminingtoolsandtechniquewereapplied.
4.5 Outlier detection
Consolidationisamethodofdataminingthatrequiresthe identificationofrelateddataaccordingtoitssimilarityand similarity. It relies on a visual approach that reflects the distribution of data towards the people so that they can understandit.
Separationrepresentsadataminingprocessthatrequires thecollectionofvariousinformationandqualitativedatafor analysis.Oncetheattributesareidentified,thedatacanbe sortedandmanaged
4.6 Sequential Pattern
5. RESULTS AND DISCUSSION
4.2 Classification
Externaldiscoveryorconfusingdiscoveryinvolveslooking atdataobjectsinadatasetofanyconfusionthatdoesnot conformtocertainbehaviors.Foranyconfusionidentified,it will be easierto understand thecausesof thisdisorder to preventit
5.6 Diseases Prediction
5.1 Patient Registration
Reports will be generated based on all analysis made previouslyandthen BMIandReportwillbeshownonthe finalstageofapplication
Patientcansecurelylogoutaftercompletingitstask.
5.2 Patient Login
The best source and fastest methods with a single mouse click.Additionalcurriculumsuchastestquestionsandany important dates will also inform you with the help of the eventwindow.Unlimitedresourcesareavailableandcanget asmuchasyouwantand,itcansaveyoutime.E learningis real timeavailable24*7days.Studentsalsogetbettertime managementasiftheyarefree,itmeansthereisnoother workandtheywillstartclasses.
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canplayanimportantroleindiseaseforecasting inordertodesignanintelligenthealthguessingsystem.In medical diagnostics, data mining has been widely used to predict diseases by diagnosis. However, there is no single data mining algorithm that is better suited to solve the problemsofguessinghealthcaredatasets.Inconclusion,a combination of a few data mining or a hybrid versionof a dataminingalgorithmmaybethebestwaytodesignalife forecast system. Future research may be focused on developingabetterdata basedmodelthatcanaddresshealth carewithreal timehealthcaredatabases.
Thisstudydoesnotincludeacompleteanalysisofallexisting dataminingalgorithmsandreal timehealthcaredatabases. Inaddition,theproposedhealthforecastsystemisnotbased oncomparingallofthedataminingalgorithmsfoundinthe literature. However, future research may be directed at selectingadataminingalgorithmthatismostrelevanttothe analysisofallexistingalgorithms.
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Theproposedsystemneedstoincludethefunctionality:
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Based on the findings of the book review, many health forecastingsystemscontainapproximatelyonedatamining algorithmstopredictdiseaseswithallindicatingtheNaïve Bayesalgorithmtobethemostefficientandaccuratedata miningalgorithm.anotherdataminingalgorithm.Typically, a data mining algorithm will be considered and selected depending on the size of the data to be tested for its predictiveaccuracy.
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5.7 Results
5.8 Logout
Allthesymptomsandpastdiseaseswillbelistedifanyfor theclarificationinprediction.
6. CONCLUSIONS
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Patientcanselectthediseases,symptomsandcanprovide fewpersonaldetailswhichislistedontheapplication
Patients will need to log in to their system with their usernameandpassword
5.5 Selection of Disease Selection
Volume: 09 Issue: 03 | Mar 2022 www.irjet.net
Thesystemcanbefurtherdevelopedbyaddingcomponents ofthesimplifiedintelligencesystemtodoctorsandpatients. Data,whichincludesthemedicalhistoryofmultiplepatient parametersandrelatedoutcomes,canbeevaluatedusingan algorithm, searching for static patterns and systematic relationships in these diseases. For example, if a patient's healthlimitschangeaccordinglyasapreviouspatientona website, the results can also be measured. If the same patternsarefoundrepeatedly,itmaybeeasierformedical researcherstofindasolutiontothisproblem.
Thehealthcaresystemhasbeenproventobeprudentand benefits all physicians and medical professionals by eliminatingtheuseoftimeandproblemsintheirdecision making process while diagnosing a patient. Various data miningmodelsneedtobeconsideredandcomparedinorder tocreateasmartlifepredictionsystem.
Patient can use the live chat functionality for any kind of clarifications or helps which will be required for the application.
5.4 Viewing Diseases/Symptoms Details
Patients will need to register themselves first with their usernameandpasswordinordertousethesystem.
Based on the patient diseases, symptoms and personal detailslikeheightandweights,decisionswillbemade
Atthatpointthemindisfreetounderstandbetter.withthe effectsofthehighlightedposters,theywillbeinspiredand will work hard to hang his image on the bulletin board. It also improves visual communication and interaction. Students adapt to the conditions in which they find themselvesinanyfieldandcancompetewiththeirexams.
Inthispaper,wepresentandvalidateanautomatedsystem prototype that ensures continuous monitoring of various health parameters and predicts any kind of illnesses or disorders that prevent the patient from experiencing frequenthospitalvisit.Theproposedsystemcanbesetupin hospitalsorathome(Anywhere)withlargeamountsofdata canbeobtainedandstoredonanonlinewebsite.Eventhe resultscanbemadeavailableonmobilephonesusingaweb
5.3 Live Chat
Dataapplicationmining
[7]J.M.A.,Calero,&J.G.,Aguado,J.G.(2015).Comparative analysisofcloudcomputinginfrastructure.
[8] J., Han, J., M., Kamber, & L., Pei (2011). Data mining: conceptsandstrategies:conceptsandstrategies.
[9]August(2010).OrdinalPhaseDataAnalysis,WileySeries onPossibleandStatistics.
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[6]A.M.,Rahman,&R.M.Rahman(2013),E Negotiationfor Resource Allocation in Grid Computing. International JournalofGridandEffectiveComputer.
[10]K.M.,Chandy&C.H.,Sauer(1978).LimitedMethodsfor AnalyzingNetworkModelsinComputerSystemRows.
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Parentsalsoreporttotheirchildrenandmonitorclassrooms there is no opportunity to cover classes because their parentsalsohaveIDsthatlookatstudentsworking.
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[5] Lehpamer (2010), Basic Network Transmission, MicrowaveTransmissionNetworks.
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[3] Mark W. Storer Kevin G D D. E. Long Ethan L. Miller (2008).October31,2008,Fairfax,Virginia,USA.2008
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[4]W.K.,Brotby.(2009).InformationSecurityManagement Metrics: A Sure Guide to Effective Security Monitoring andEvaluation.
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[1]YunhongGu,RobertLD.2009.Grossman.Sector,public data storage and sharing system. future Computer Systems,20May2009.
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