Set Operations in Python for Translational Medicine

This is the world’s first tutorial article on Python programing on set operations for beginners and practitioners in translational medicine or medicine in general. This tutorial will allow researchers to demonstrate and showcase their tools on PyPI packages around the world. Via the PyPI packaging,...

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Vydáno v:International journal of translational medicine Ročník 2; číslo 2; s. 174 - 185
Hlavní autor: Takefuji, Yoshiyasu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Jackson MDPI AG 29.04.2022
Témata:
Age groups
Code Ocean
Coronaviruses
COVID-19 vaccines
dataset
Datasets
Gender
Keywords
Linux
Medicine
Open source software
Packaging
Patients
PyPI package
Python program
Reproducibility
Software upgrading
translational medicine
VAERS
Windows operating system
ISSN:2673-8937, 2673-8937
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Shrnutí:This is the world’s first tutorial article on Python programing on set operations for beginners and practitioners in translational medicine or medicine in general. This tutorial will allow researchers to demonstrate and showcase their tools on PyPI packages around the world. Via the PyPI packaging, a Python application with a single source code can run on Windows, MacOS, and Linux operating systems. In addition to the PyPI packaging, the reproducibility and quality of the source code must be guaranteed. This paper shows how to publish the Python application in Code Ocean after the PyPI packaging. Code Ocean is used in IEEE, Springer, and Elsevier for software reproducibility validation. First, programmers must understand how to scrape a dataset over the Internet. Second, the dataset files must be read in Python. Third, a program must be built to compute the target values using set operations. Fourth, the Python program must be converted to the PyPI package. Finally, the PyPI package is uploaded. Code Ocean plays a key role in publishing validation for software reproducibility. This paper depicts a vaers executable package as an example for calculating the number of deaths due to COVID-19 vaccines. Calculations were based on gender (male and female), age group, and vaccine group (Moderna, Pfizer, and Novartis), respectively.
Bibliografie:ObjectType-Article-1
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ISSN:2673-8937
2673-8937
DOI:10.3390/ijtm2020015