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app.py 1
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app.py
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@@ -1,4 +1,3 @@
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def main(Pregnancies,Glucose_level,BP,skin_thickness,Insulin,BMI,Diabetes_Function,Age):
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import numpy as np # linear algebra
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import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
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import matplotlib.pyplot as plt
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@@ -8,6 +7,8 @@ def main(Pregnancies,Glucose_level,BP,skin_thickness,Insulin,BMI,Diabetes_Functi
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from sklearn.metrics import accuracy_score
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from sklearn.model_selection import cross_val_score
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from sklearn.metrics import r2_score
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url="https://raw.githubusercontent.com/ADITHYASNAIR2021/Dataset-cart/main/diabetes.csv"
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diabetes_df = pd.read_csv(url)
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@@ -101,17 +102,17 @@ examples=[[2,120,120,25,20,25,1,25],[5,200,200,50,160,30,2,30]],
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description =''' Description
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Some health issues are more serious than others. An example of a severe health issue is diabetes, which is an all-too-common condition
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It is
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resulting in complications such as nerve damage, kidney damage, heart attacks, strokes, peripheral vascular disease etc. While some risk factors of
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developing diabetes cannot be changed,
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As we face these high numbers of diabetes and prediabetes cases, it’s important that everyone learns as much as they can about recognizing and preventing diabetes.
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All these points emphasise that diabetes can be really bad if not diagnosed properly so,
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with this AI tool, we can predict the onset of diabetes among people which will help them to adjust their lifestyles and other things correctly to prevent
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Output0 - Describes the Prediction made
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Output1 - Analyse
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Output2 - Analysis of Glucose level
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@@ -141,7 +142,7 @@ Therefore, there is one target (dependent) variable and the following attributes
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* Age (years)
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* Pedigree Diabetes Function ('function that represents how likely they are to get the disease by extrapolating from their ancestor’s history )
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Generally,
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To know more about the Tricep skin fold thickness measure
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visit this link:- https://ibb.co/4NDNNx1
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import numpy as np # linear algebra
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import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
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import matplotlib.pyplot as plt
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from sklearn.metrics import accuracy_score
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from sklearn.model_selection import cross_val_score
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from sklearn.metrics import r2_score
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def main(Pregnancies,Glucose_level,BP,skin_thickness,Insulin,BMI,Diabetes_Function,Age):
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url="https://raw.githubusercontent.com/ADITHYASNAIR2021/Dataset-cart/main/diabetes.csv"
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diabetes_df = pd.read_csv(url)
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description =''' Description
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Some health issues are more serious than others. An example of a severe health issue is diabetes, which is an all-too-common condition
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It is essential for people with diabetes to be diagnosed and treated as soon as possible, as high blood sugar levels can damage body organs and tissue,
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resulting in complications such as nerve damage, kidney damage, heart attacks, strokes, peripheral vascular disease etc. While some risk factors of
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developing diabetes cannot be changed, healthy lifestyle choices can dramatically reduce a person’s chances of developing it.
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As we face these high numbers of diabetes and prediabetes cases, it’s important that everyone learns as much as they can about recognizing and preventing diabetes.
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All these points emphasise that diabetes can be really bad if not diagnosed properly so,
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with this AI tool, we can predict the onset of diabetes among people which will help them to adjust their lifestyles and other things correctly to prevent diabetes in the future.
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Output0 - Describes the Prediction made
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Output1 - Analyse BMI
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Output2 - Analysis of Glucose level
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* Age (years)
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* Pedigree Diabetes Function ('function that represents how likely they are to get the disease by extrapolating from their ancestor’s history )
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Generally, it's between 0 - 2.5, if there wasn't any ancestorial history of diabetes you can choose between 0 and 1, and if there is any so can select between 1 - 2.5 regarding the seriousness in the family.
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To know more about the Tricep skin fold thickness measure
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visit this link:- https://ibb.co/4NDNNx1
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