model.ipynb

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   "cell_type": "code",
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   "source": [
    "import pandas as pd\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# Load data\n",
    "df = pd.read_csv(r\"D:\\processed-data.csv\")\n",
    "\n",
    "# Drop unnecessary columns using column indexing and rename the target column\n",
    "df = df.drop(df.columns[[4, 5]], axis=1)  # Drop columns by index\n",
    "df.rename(columns={'Severity_None': 'Target'}, inplace=True)\n",
    "\n",
    "# Prepare data for training and testing\n",
    "x = df.drop(columns=['Target'])  # Features\n",
    "y = df['Target']  # Target variable: 'Target' column represents severity levels\n",
    "\n",
    "# Split data into training and testing sets\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Initialize the Gradient Boosting Classifier with adjusted hyperparameters\n",
    "model = GradientBoostingClassifier(\n",
    "    n_estimators=100,  # Increase the number of estimators\n",
    "    learning_rate=0.1,  # Adjust the learning rate\n",
    "    max_depth=5,  # Increase the maximum depth of the trees\n",
    "    min_samples_split=2,\n",
    "    min_samples_leaf=1,\n",
    "    random_state=42,\n",
    ")\n",
    "\n",
    "# Train the model\n",
    "model.fit(x_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b3c4d5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to map 'yes' or 'no' inputs to integers\n",
    "def map_yes_no_to_int(answer):\n",
    "    if answer.lower() == 'yes':\n",
    "        return 1\n",
    "    elif answer.lower() == 'no':\n",
    "        return 0\n",
    "    else:\n",
    "        raise ValueError(\"Invalid input! Please enter 'yes' or 'no'.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3c4d5e6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to check threshold based on symptoms, age, and gender\n",
    "def check_threshold(symptoms, age, gender):\n",
    "    if all(symptoms) and age >= 60:\n",
    "        return True\n",
    "    elif all(symptoms) and age < 11:\n",
    "        return True\n",
    "    elif all(symptoms):\n",
    "        return True\n",
    "    elif not any(symptoms) and gender == 'male' and age >= 25:\n",
    "        return False\n",
    "    else:\n",
    "        return False\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d5e6f7g",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to get recommendation based on severity prediction\n",
    "def get_recommendation(severity):\n",
    "    if severity == 0:\n",
    "        return 'Your asthma condition is currently under control. Continue to monitor your symptoms regularly.'\n",
    "    elif severity == 1 or severity == 2:\n",
    "        return '''You are experiencing mild to moderate asthma symptoms. Try some home remedies such as:\n",
    "            1. Steam Inhalation: Inhale steam from hot water to open up the airways.\n",
    "            2. Staying Hydrated: Drink plenty of water to keep the airways moist.\n",
    "            3. Using a Humidifier: Add moisture to the air with a humidifier to prevent dryness in the airways.\n",
    "            4. Breathing Exercises: Practice deep breathing exercises and pursed-lip breathing to improve lung function.\n",
    "            5. Avoiding Triggers: Identify and avoid triggers such as smoke, dust, pollen, and pet dander.\n",
    "            6. Maintaining a Clean Environment: Keep the home clean and free of dust, mold, and allergens.'''\n",
    "    elif severity == 3:\n",
    "        return '''You are experiencing severe asthma symptoms. Please seek immediate medical attention. In the meantime, you may find the following resources helpful:\n",
    "            1. [How to ease asthma symptoms - 3 effective breathing exercises by Airofit](https://www.youtube.com/watch?v=FyjZLPmZ534)\n",
    "            2. [Exercise-Induced Asthma by CNN](https://www.youtube.com/watch?v=B8pNeYFZNew)\n",
    "            3. [ASTHMA / how to cure exercise induced wheezing naturally by Andrew Folts](https://www.youtube.com/watch?v=jv-revgQdPE)\n",
    "            4. [Easy tips to treat Asthma & Bronchitis | Dr. Hansaji Yogendra by The Yoga Institute](https://www.youtube.com/watch?v=JwRG8AsStLQ)\n",
    "            5. [Breathing Exercises for COPD, Asthma, Bronchitis & Emphysema - Ask Doctor Jo by AskDoctorJo](https://www.youtube.com/watch?v=dpTNUGwXbTU)'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5e6f7g8h",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to perform prediction\n",
    "def predict_asthma(name, tiredness, dry_cough, difficulty_breathing, sore_throat, nasal_congestion, runny_nose, age, gender):\n",
    "    try:\n",
    "        tiredness = map_yes_no_to_int(tiredness)\n",
    "        dry_cough = map_yes_no_to_int(dry_cough)\n",
    "        difficulty_breathing = map_yes_no_to_int(difficulty_breathing)\n",
    "        sore_throat = map_yes_no_to_int(sore_throat)\n",
    "        nasal_congestion = map_yes_no_to_int(nasal_congestion)\n",
    "        runny_nose = map_yes_no_to_int(runny_nose)\n",
    "        age = int(age)\n",
    "\n",
    "        # Check if all symptoms are 'no'\n",
    "        if tiredness == dry_cough == difficulty_breathing == sore_throat == nasal_congestion == runny_nose == 0:\n",
    "            severity_prediction = 0\n",
    "        else:\n",
    "            symptoms = [tiredness, dry_cough, difficulty_breathing, sore_throat, nasal_congestion, runny_nose]\n",
    "            if check_threshold(symptoms, age, gender):\n",
    "                severity_prediction = 3  # Set severity to maximum if threshold is met\n",
    "            else:\n",
    "                none_experiencing = 1 if sum(symptoms) == 0 else 0\n",
    "                user_input = [tiredness, dry_cough, difficulty_breathing, sore_throat, nasal_congestion, runny_nose,\n",
    "                              none_experiencing,  # None_Experiencing feature\n",
    "                              1 if age <= 9 else 0,  # Age_0-9 feature\n",
    "                              1 if age >= 10 and age <= 19 else 0,  # Age_10-19 feature\n",
    "                              1 if age >= 20 and age <= 24 else 0,  # Age_20-24 feature\n",
    "                              1 if age >= 25 and age <= 59 else 0,  # Age_25-59 feature\n",
    "                              1 if age >= 60 else 0,  # Age_60+ feature\n",
    "                              1 if gender == 'female' else 0,  # Gender_Female feature\n",
    "                              1 if gender == 'male' else 0,  # Gender_Male feature\n",
    "                              0,  # Severity_Mild placeholder\n",
    "                              0]  # Severity_Moderate placeholder\n",
    "                severity_prediction = model.predict([user_input])[0]\n",
    "\n",
    "        recommendation = get_recommendation(severity_prediction)\n",
    "\n",
    "        return f\"Hello {name}!\\nSeverity Prediction: {severity_prediction}\\nRecommendation: {recommendation}\\nGender: {gender}\"\n",
    "\n",
    "    except Exception as e:\n",
    "        return f\"An error occurred: {str(e)}\"\n"
   ]
  }
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