The aim of this project is to find whether a symptom or a set of symptoms among a paediatric patient can be conclusive to diagnose or refute SARS-CoV-2. In order to achieve so, a dataset with over 1600 cases has been studied with Python3. It has also been attempted to create the files as comprehensible as possible for a third person willing to make use of the codes. GREATER DETAIL ON THE WIKI!
This project relies strongly on plotting and analysing data, and thus some external libraries had to be imported:
- matplotlib
- numpy
If these are not installed on the system, do NOT expect the program to work
All algorithms and files found in this project are capable of working with different datasets or conditions without having to retype a myriad of modifications.
It is the main file of the project, and it calculates the probability of having SARS-CoV-2 by combining them. By the moment, it is capable of separating between gender, positive and negative diagnosis.
This file is a simple python script to retrieve a given field from the dataset and indicate its position. It is necessary as the dictionary provided was not completely precise.
Here one can find some arrays that can aid you in looking for correlations or incompatibilities between COVID and other infections/medical conditions.
This file contains a simple python algorithm that looks for the correlations mentioned above. It also contains a short program that calculates the probability of contacting COVID together with other conditions.
Under the directory Files/ one can expect to find the dataset (extension .csv) with over 1600 paediatric patients.
Under the directory Output/ some .txt files are stored. These contain the list of probabilities of having SARS-CoV-2 when presenting two different symptoms. There are a total of three files, being GenderAwareProbabilities.txt and GenderUnawareProbabilities.txt the two files with the whole list of combinations considered.