library(shiny)
library(shinydashboard)
library(gbm)
library(caret)
library(caretEnsemble)
ui <- fluidPage(
dashboardPage(
dashboardHeader(title="Basic Dashboard",
dropdownMenu(type = "messages",
messageItem(
from = "Personal Doctor",
message = "Please schedule an Appointment if there is any issue"
),
messageItem(
from = "New User",
message = "How do I use the Dashboard?",
icon = icon("question"),
time = "13:45"
),
messageItem(
from = "Support",
message = "The new server is ready.",
icon = icon("life-ring"),
time = "2020-05-13"
)
),
dropdownMenu(type = "notifications",
notificationItem(
text = "7 new users today",
icon("users")
),
notificationItem(
text = "5 Doctors are available ",
icon("hospital"),
status = "success"
),
notificationItem(
text = "Server load at 97%",
icon = icon("exclamation-triangle"),
status = "warning"
)
),
dropdownMenu(type = "tasks", badgeStatus = "success",
taskItem(value = 90, color = "green",
"Heart Disease"
)
)),
#Sidebar Content
dashboardSidebar(
sidebarMenu(
menuItem("Heart Disease",tabName = "Heart Disease",icon=icon("dashboard"))
)
),
dashboardBody(
fluidRow(
valueBoxOutput("age"),
valueBoxOutput("gender"),
valueBoxOutput("BMI")
),
box(
title="Your Probability of Having Heart Disease is:",
textOutput("Pred")
),
box(
title = "Please Fill in the Following to Get the Likelihood of Having Heart Disease",status="danger",background="navy", solidHeader = TRUE,
numericInput(inputId='age',
label='1.Please Enter your Age:',
value=NA,min = NA,
max = NA, step = NA,
width = NULL),
checkboxGroupInput(inputId='sex',
label='Please check your gender:',
c('female','male'),
selected = NULL,
inline = FALSE,width = NULL),
numericInput(inputId='weight',
label='1.Please Enter your Weight:',
value =NA ,min = NA,
max = NA, step = NA,
width = NULL),
numericInput(inputId='height',
label='1.Please Enter your Height:',
value =NA ,min = NA,
max = NA, step = NA,
width = NULL),
checkboxGroupInput(inputId = 'cp',label='Please describe the type of chest pain you have experienced:',
c('normal pains','extreme pain','no pains','asymptomatic pain'),
selected=NULL,
inline = FALSE,width=NULL),
numericInput('trestbps',label='Please Enter your resting blood pressure in mm/Hg:',
min=50,
max=200,
value = 120),
numericInput(inputId = 'chol',label='Please enter your cholestrol levels:',
value=203,
min=80,
max=NA,
step=NA,
width=NULL),
),
box(
title = "Please Fill in the Following to Get the Likelihood of Having Heart Disease",status="danger",background="navy", solidHeader = TRUE,
checkboxGroupInput(inputId = 'fbs',label='How can you describe your blood sugar levels after fasting:',
c('normal','abnormal'),selected=NULL,
inline=FALSE,width=NULL),
checkboxGroupInput(inputId = 'restecg',label='How is your breathing when you are resting?',
c('normal','probable difficulties','difficult'),
selected=NULL,
inline=FALSE,width=NULL),
numericInput(inputId = 'thalach',label='what is the maximum heart rate you can achieve?',
value=100,
min=71,
max=NA,
step=NA,
width=NULL),
checkboxGroupInput(inputId = 'exang',label='Have you experienced any chest pains after exercising?',
c('no','yes'),selected=NULL,
inline = FALSE,
width = NULL),
checkboxGroupInput(inputId = 'ca',label='Have you had any blood circulation problems?',
c('all the time','a few times','quite a few times','almost never','never'),selected=NULL,
inline=FALSE,
width=NULL),
checkboxGroupInput(inputId = 'thal',label = 'How can you describe the nature of your blood?',
c('has unknown defect','is normal','has fixed defects','has reversible defects'),
selected=NULL,
inline = FALSE,
width=NULL)
)
)
)
)
server <- function(input, output,session) {
output$age <- renderValueBox({
valueBox(
paste0(input$age), "Age", icon = icon("thumbs-up"),
color = "light-blue"
)
})
output$gender <- renderValueBox({
valueBox(
paste0(input$sex),"Gender",icon = icon("list"),
color = "aqua"
)
})
output$BMI <- renderValueBox({
valueBox(
paste0(input$weight/(input$height^2)), "Body Mass Index(BMI)", icon = icon("ambulance"),
color = "blue"
)
})
model<-readRDS("F:/Project Machine learning/Saved Models/model_gbm.RDS")
data<-reactive({
req(input$sex)
req(input$cp)
req(input$fbs)
req(input$restecg)
req(input$exang)
req(input$ca)
req(input$thal)
req(input$age)
req(input$trestbps)
req(input$chol)
req(input$thalach)
df_final= data.frame(
age=input$age,
sex=input$sex,
cp=input$cp,
trestbps=input$trestbps,
chol=input$chol,
fbs=input$fbs,
restecg=input$restecg,
thalach=input$thalach,
exang=input$exang,
ca=input$ca,
thal=input$thal)
})
pred=reactive({predict(model,data(),type="response")})
output$Pred <- renderPrint(pred())
}
shinyApp(ui, server)
It keeps on bringing the error of;
Warning: Error in predict.train: type must be either "raw" or "prob" 119: stop 118: predict.train 116: [F:\Project Machine learning\kristophe/app.R#190] 100: pred 99: renderPrint 98: func 82: origRenderFunc 81: output$Pred 1: shiny::runApp
Dont know what the problem could be.
