Symptom Analysis and Disease Prediction

Exploring Various Machine Learning Algorithms to possibily predict the Disease of the Patient based on their Symptoms Reported.

DataSets

Final Working Data set is sourced from another GitCommit. You can find them in Data Set (Main) folder.

Also there are some other Data Sets that were used as References for this Project. You can find them in Data Set (Referred) folder

Requierments for the Project

Anaconda Suite

Download the Anaconda Distribution for your Working Platform (Windows / Linux / macOS) from here

Visual Studio / Visual Studio Code

Alternatively, you can use any other Code Editor (recommended Visual Studio Code) - but make sure you have the below listed Python Modules installed

Visual Studio Code make use of integrated python Terminal - which is similar to pip. So, you can install the packages with command like :

pip install <package-name>

Numpy

Numpy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

Install numpy by :

pip install numpy

Pandas

pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.

Install pandas by :

pip install pandas

Scikit-Learn

Scikit-learn (a.k.a. sklearn) is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Install scikit-learn by :

pip install -U scikit-learn

In order to check your installation you can use

pip show scikit-learn  # to see which version and where scikit-learn is installed
python -c "import sklearn; sklearn.show_versions()"

Matplotlib

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.

for Matplotlib and Python see Python Tutorial

Install matplotlib by :

pip install matplotlib

tkinter

tkinter (“Tk interface”) is the standard Python interface to the Tcl/Tk GUI toolkit. Both Tk and tkinter are available on most Unix platforms, including macOS, as well as on Windows systems.

Running python -m tkinter from the command line should open a window demonstrating a simple Tk interface, letting you know that tkinter is properly installed on your system, and also showing what version of Tcl/Tk is installed.

tkinter is an in-build library module - installation is not required

Running the Project

Running on Anaconda

1. Open Anaconada Distribution and find Spyder IDE.

2. Load the MainCode.py and run through the Code for any errors

Note: Before Running, Make sure that both Data Set (Testing.csv and Training.csv) and MainCode.py reside under the same folder!

3. Lookup for an Option saying "Run in New Kernel" and run the Code

Running on Visual Studio / Visual Studio Code

Get it Done with a Click

1. Search for the extension "Code Runner" in Visual Studio Code or you can head to Microsoft Marketplace or GitHub

2. After instaling the Extension you can run the MainCode.py from the Run button that pops on the Top Right Corner of the Editor

Terminal Way

In Terminal you can also Run the Code as below :

& <path-to-python-installation-directory>/python.exe <path-to-code>/MainCode.py