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| import pandas as pd | |
| import gradio as gr | |
| import numpy as np | |
| import seaborn as sns | |
| import matplotlib.pyplot as plt | |
| import sklearn | |
| from sklearn import tree | |
| from sklearn.linear_model import LinearRegression | |
| from sklearn.linear_model import LogisticRegression | |
| from sklearn.tree import DecisionTreeClassifier | |
| from sklearn.preprocessing import scale | |
| from sklearn.model_selection import train_test_split | |
| from sklearn.metrics import confusion_matrix | |
| from sklearn.preprocessing import StandardScaler | |
| def main(Follicle_No_Right,Follicle_No_Left,Skin_darkening,Hair_growth,Weight_gain,Cycle): | |
| url="https://raw.githubusercontent.com/Athulg19/datasets/main/PCOS_clean_data_without_infertility.csv" | |
| data = pd.read_csv(url) | |
| data=pd.DataFrame(data) | |
| data=data.astype(np.float64) | |
| data.dtypes | |
| correlation=data.corrwith(data['PCOS (Y/N)']).abs().sort_values(ascending=False) | |
| correlation=correlation[correlation>0.4].index | |
| data=data[correlation] | |
| arr=data.values | |
| X=arr[:,1:6] | |
| Y=arr[:,0] | |
| scaler=StandardScaler().fit(X) | |
| rescaledX=scaler.transform(X) | |
| np.set_printoptions(precision=3) | |
| y=data['PCOS (Y/N)'] | |
| x=data.drop(['PCOS (Y/N)'],axis=1) | |
| X_train,X_test,y_train,y_test = train_test_split(x,y,test_size=.25) | |
| logistic = LogisticRegression() | |
| logistic.fit(X_train,y_train) | |
| data = {'Follicle No. (R)':Follicle_No_Right,'Follicle No. (L)':Follicle_No_Left,'Skin darkening (Y/N)':Skin_darkening,'hair growth(Y/N)':Hair_growth,'Weight gain(Y/N)':Weight_gain,'Cycle(R/I)':Cycle} | |
| index = [0] | |
| cust_df = pd.DataFrame(data, index) | |
| costpredLog = logistic.predict(cust_df) | |
| if costpredLog ==0: | |
| Prediction = "There is less chance for the patient to catch PCOS" | |
| else: | |
| Prediction = "There is more chance for the patient to catch PCOS." | |
| return Prediction | |
| iface = gr.Interface(fn = main, | |
| inputs =['number','number','number','number','number','number'], | |
| outputs =['text'], | |
| title="Onset of PCOS prediction", | |
| description =''' Description | |
| Polycystic ovary syndrome (PCOS) is a problem with hormones that happens during the reproductive years. If you have PCOS, you may not have periods very often. | |
| Or you may have periods that last many days. You may also have too much of a hormone called androgen in your body. | |
| With PCOS, many small sacs of fluid develop along the outer edge of the ovary. These are called cysts. The small fluid-filled cysts contain immature eggs. | |
| These are called follicles. The follicles fail to regularly release eggs. | |
| The exact cause of PCOS is unknown. Early diagnosis and treatment along with weight loss may lower the risk of long-term complications such as type 2 diabetes and heart disease. | |
| Output0 - Describes the Prediction made | |
| More details about the Inputs taken and how they needed to be taken are given below: | |
| Follicle_No_Right = Number of follicles is in Right Overy | |
| Follicle_No_Left = Number of follicles is in Left Ovary | |
| Skin_darkening = yes(1)/No(0) | |
| Hair_growth = yes(1)/No(0) | |
| Weight_gain = yes(1)/No(0) | |
| Cycle = If it is Regular (0) or Irregular (1) | |
| ''', | |
| article=''' | |
| Complications of PCOS can include: | |
| * Infertility | |
| * Gestational diabetes or pregnancy-induced high blood pressure | |
| * Miscarriage or premature birth | |
| * Nonalcoholic steatohepatitis — a severe liver inflammation caused by fat accumulation in the liver | |
| * Metabolic syndrome — a cluster of conditions including high blood pressure, | |
| high blood sugar, and abnormal cholesterol or triglyceride levels that significantly increase your risk of cardiovascular disease | |
| * Type 2 diabetes or prediabetes | |
| * Sleep apnea | |
| * Depression, anxiety and eating disorders | |
| * Abnormal uterine bleeding | |
| * Cancer of the uterine lining (endometrial cancer)''') | |
| iface.launch(debug =True) |