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Platinum.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Platinum.ipynb",
+      "provenance": [],
+      "collapsed_sections": [],
+      "authorship_tag": "ABX9TyO1l5XXdyXWCTVcO6/be7EV"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "sLPCsQmoV8xs"
+      },
+      "source": [
+        "# Platinum heart & liver disease predictor\n",
+        "Class 12 CS project by Aryan Patil, Priyansh Mishra and Rithwik Anand"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "7Dg7a2vVHZos"
+      },
+      "source": [
+        "#github.com/realaryanpatil/Platinum"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "7XpVe5YIYVJt"
+      },
+      "source": [
+        "### This program requires datasets to work. Please download liver.csv and heart.csv from the [repository](https://github.com/realaryanpatil/Platinum) "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "YEWYKEaNY-Ed"
+      },
+      "source": [
+        "import pandas as pd\n",
+        "\n",
+        "def trainheart(q1,q2,q3,q4,q5,q6,q7,q8,q9,q10,q11):\n",
+        "  dataset = pd.read_csv('medical.csv')\n",
+        "  X = dataset.iloc[:, :-1].values\n",
+        "  y = dataset.iloc[:, -1].values\n",
+        "    \n",
+        "  from sklearn.model_selection import train_test_split\n",
+        "  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3, random_state = 0)\n",
+        "\n",
+        "  from sklearn.preprocessing import StandardScaler\n",
+        "  sc = StandardScaler()\n",
+        "  X_train = sc.fit_transform(X_train)\n",
+        "  X_test = sc.transform(X_test)\n",
+        "\n",
+        "  from sklearn.naive_bayes import GaussianNB\n",
+        "  classifier = GaussianNB()\n",
+        "  classifier.fit(X_train, y_train)\n",
+        "\n",
+        "  result = classifier.predict(sc.transform([[q1,q2,q3,q4,q5,q6,q7,q8,q9,q10,q11]]))\n",
+        "  output = int(result)\n",
+        "  if output == 1:\n",
+        "    a1 = \"The patient is at a high risk of heart failure.\"\n",
+        "  else:\n",
+        "    a1 = \"The patient is at a low risk of heart failure.\"\n",
+        "  print(a1)\n",
+        "\n",
+        "def livertrain(q1,q2,q3,q4,q5,q6,q7,q8,q9,q10):\n",
+        "  dataset = pd.read_csv('liver.csv')\n",
+        "  X = dataset.iloc[:, :-1].values\n",
+        "  y = dataset.iloc[:, -1].values\n",
+        "    \n",
+        "  from sklearn.model_selection import train_test_split\n",
+        "  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0)\n",
+        "\n",
+        "  from sklearn.preprocessing import StandardScaler\n",
+        "  sc = StandardScaler()\n",
+        "  X_train = sc.fit_transform(X_train)\n",
+        "  X_test = sc.transform(X_test)\n",
+        "\n",
+        "  from sklearn.naive_bayes import GaussianNB\n",
+        "  classifier = GaussianNB()\n",
+        "  classifier.fit(X_train, y_train)\n",
+        "\n",
+        "  result = classifier.predict(sc.transform([[q1,q2,q3,q4,q5,q6,q7,q8,q9,q10]]))\n",
+        "  output = int(result)\n",
+        "  if output == 1:\n",
+        "    a1 = \"The patient is at a high risk of liver disease.\"\n",
+        "  else:\n",
+        "    a1 = \"The patient is at a low risk of liver disease.\"\n",
+        "  print(a1)\n",
+        "\n",
+        "question = input(\"\"\"Welcome to Platinum Argos [V1.0], A Naive Bayes classification system to detect heart/liver disease.\n",
+        "\n",
+        "Please select your choice below:\n",
+        "[1] Heart failure risk analysis\n",
+        "[2] Liver disease risk analysis\n",
+        "--------------------------------------------------------------------------------------------------\n",
+        ":\"\"\")\n",
+        "\n",
+        "if question == '1' or question == 'heart':\n",
+        "  print('---------------------------------------heart-----------------------------------------------')\n",
+        "  r1 = input(\"Patient age: \")\n",
+        "  r2 = input(\"Is the patient suffering from anemia? (y/n): \")\n",
+        "  if r2 == 'y':\n",
+        "    r2 = 1\n",
+        "  else:\n",
+        "    r2 = 0\n",
+        "  r3 = input(\"Creatine Phosphokinase levels (in micrograms per litre): \")\n",
+        "  r4 = input(\"Is the patient suffering from diabetes? (y/n): \")\n",
+        "  if r4 == 'y':\n",
+        "    r4 = 1\n",
+        "  else:\n",
+        "    r4 = 0\n",
+        "  r5 = input(\"Ejection Fraction (in %): \")\n",
+        "  r6 = input(\"Is the patient suffering from hypertension? (y/n): \")\n",
+        "  if r6 == 'y':\n",
+        "    r6 = 1\n",
+        "  else:\n",
+        "    r6 = 0\n",
+        "  r7 = input(\"Number of platelets: \")\n",
+        "  r8 = input(\"Serum Creatine levels: \")\n",
+        "  r9 = input(\"Serum Sodium levels: \")\n",
+        "  r10 = input(\"Gender (m/f): \")\n",
+        "  if r10 == 'm':\n",
+        "    r10 = 1\n",
+        "  else:\n",
+        "    r10 = 0\n",
+        "  r11 = input(\"Does the patient smoke? (y/n): \")\n",
+        "  if r11 == 'y':\n",
+        "    r11 = 1\n",
+        "  else:\n",
+        "    r11 = 0\n",
+        "\n",
+        "  trainheart(r1,r2,r3,r4,r5,r6,r7,r8,r9,r10,r11)\n",
+        "\n",
+        "elif question == \"2\" or question == \"liver\":\n",
+        "  print('---------------------------------------liver-----------------------------------------------')\n",
+        "  r1 = input(\"Patient age: \")\n",
+        "  r2 = input(\"Patient gender (m/f): \")\n",
+        "  if r2 == 'm':\n",
+        "    r2 = 1\n",
+        "  else:\n",
+        "    r2 = 0\n",
+        "  r3 = input(\"Total Bilirubin: \")\n",
+        "  r4 = input(\"Direct Bilirubin: \")\n",
+        "  r5 = input(\"Alkaline Phosphotase: \")\n",
+        "  r6 = input(\"Alamine Aminotransferase:\")\n",
+        "  r7 = input(\"Aspartate Aminotransferase: \")\n",
+        "  r8 = input(\"Total Protiens: \")\n",
+        "  r9 = input(\"Albumin levels: \")\n",
+        "  r10 = input(\"Albumin and Globulin Ratio: \")\n",
+        "\n",
+        "  livertrain(r1,r2,r3,r4,r5,r6,r7,r8,r9,r10)\n",
+        "\n",
+        "else:\n",
+        "  print(\"Wrong input. Please try again.\")\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n"
+      ],
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}