Update app.py

app.py

@@ -1,37 +1,9 @@
-
 import streamlit as st
 import re
 import pandas as pd
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.naive_bayes import MultinomialNB
-import numpy as np
 from sklearn.model_selection import train_test_split
-from sklearn.ensemble import RandomForestClassifier
-from sklearn.metrics import accuracy_score, classification_report
-import tensorflow as tf
-from sklearn.feature_extraction.text import TfidfVectorizer
-from sklearn.naive_bayes import MultinomialNB
-from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
-import nltk
-from nltk.corpus import stopwords
-from nltk.stem import PorterStemmer
-from gensim.models import Word2Vec
-import matplotlib.pyplot as plt
-import seaborn as sns
-
-
-
-# for using TensorFlow for deep learning
-from tensorflow.keras.models import Sequential
-from tensorflow.keras.layers import Dense
-from tensorflow.keras.optimizers import Adam
-from tensorflow.keras.losses import categorical_crossentropy
-
-# for using PyTorch for deep learning
-import torch
-import torch.nn as nn
-import torch.optim as optim
-import torch.nn.functional as F
 
 # Load your symptom-disease data
 data = pd.read_csv("Symptom2Disease.csv")
@@ -52,11 +24,20 @@ model = MultinomialNB()
 model.fit(X_train, y_train)
 
 # Set Streamlit app title with emojis
-st.title("Healthcare Symptom-to-Disease Recommender 🏥👨‍⚕️")
+st.title("Health Symptom-to-Disease Predictor 🏥👨‍⚕️")
 
 # Define a sidebar
 st.sidebar.title("Tool Definition")
-st.sidebar.markdown("This tool helps you identify possible diseases based on the symptoms you provide. It is not a substitute for professional medical advice. Always consult a healthcare professional for accurate diagnosis and treatment.")
+st.sidebar.markdown("This tool helps you identify possible diseases based on the symptoms you provide.")
+st.sidebar.markdown("the tool may aid healthcare professionals in the initial assessment of potential conditions, facilitating quicker decision-making and improving patient care")
+
+st.sidebar.title("⚠️ **Limitation**")
+st.sidebar.markdown("This tool's predictions are based solely on symptom descriptions and may not account for other critical factors,")
+st.sidebar.markdown("such as a patient's medical history or laboratory tests,")
+st.sidebar.markdown("As such,it should be used as an initial reference and not as a sole diagnostic tool. 👩‍⚕️")
+                    
+st.warning("Please note that this tool is for informational purposes only. Always consult a healthcare professional for accurate medical advice.")
+show_faqs = st.sidebar.checkbox("Show FAQs")
 
 # Initialize chat history
 if "messages" not in st.session_state:
@@ -97,8 +78,18 @@ if st.button("Predict Disease"):
         else:
             st.warning("Please enter your symptoms before predicting.")
 
-# Display a warning message
-st.warning("Please note that this tool is for informational purposes only. Always consult a healthcare professional for accurate medical advice.")
+# Create FAQs section
+if show_faqs:
+    st.markdown("## Frequently Asked Questions")
+    st.markdown("**Q: How does this tool work?**")
+    st.markdown("A: The tool uses a machine learning model to analyze the symptoms you enter and predicts possible diseases based on a pre-trained dataset.")
+
+    st.markdown("**Q: Is this a substitute for a doctor's advice?**")
+    st.markdown("A: No, this tool is for informational purposes only. It's essential to consult a healthcare professional for accurate medical advice.")
+
+    st.markdown("**Q: Can I trust the predictions?**")
+    st.markdown("A: While the tool provides predictions, it's not a guarantee of accuracy. It's always best to consult a healthcare expert for a reliable diagnosis.")
 
 # Add attribution
-st.markdown("Created  ❤️ by Richard Dorglo")
+st.markdown("Created  ❤️ by Richard Dorglo")
+