brain-multiple-modalities-automl 0.0.1

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brainmultiplemodalitiesautoml 0.0.1

Brain-AutoML



An open-source Python framework for systematic review based on PRISMA : systematic-reviewpy

Chaudhari, C., Purswani, G. (2023). Stock Market Prediction Techniques Using Artificial Intelligence: A Systematic Review. In: Kumar, S., Sharma, H., Balachandran, K., Kim, J.H., Bansal, J.C. (eds) Third Congress on Intelligent Systems. CIS 2022. Lecture Notes in Networks and Systems, vol 608. Springer, Singapore. https://doi.org/10.1007/978-981-19-9225-4_17


Introduction
Features
Installation
Contribution
Future Improvements

Introduction
The main objective of the Python framework is to automate systematic reviews to save reviewers time without creating
constraints that might affect the review quality. The other objective is to create an open-source and highly
customisable framework with options to use or improve any parts of the framework. python framework supports each step in
the systematic review workflow and suggests using checklists provided by Preferred Reporting Items for Systematic Reviews
and Meta-Analyses (PRISMA).
Authors

The packages systematic-reviewpy and
browser-automationpy are part of Research paper
An open-source Python framework for systematic review based on PRISMA created by Chandravesh chaudhari, Doctoral candidate at CHRIST (Deemed to be University), Bangalore, India under supervision of Dr. Geetanjali purswani.

Features

supported file types: ris, json, and pandas IO
supports the complete workflow for systematic reviews.
supports to combine multiple databases citations.
supports searching words with boolean conditions and filter based on counts.
browser automation using browser-automationpy
validation of downloaded articles.
contains natural language processing techniques such as stemming and lemmatisation for text mining.
sorting selected research papers based on database.
generating literature review excel or csv file.
automatically generates analysis tables and graphs.
automatically generates workflow diagram.
generate the ASReview supported file for Active-learning Screening

Significance

Saves time
Automate monotonous tasks
Never makes mistakes
Provides replicable results

Installation
This project is available at PyPI. For help in installation check
instructions
python3 -m pip install systematic-reviewpy

Dependencies
Required

rispy - A Python 3.6+ reader/writer of RIS reference files.
pandas - A Python package that provides fast, flexible, and expressive data
structures designed to make working with "relational" or "labeled" data both easy and intuitive.

Optional

browser-automationpy
pdftotext - Simple PDF text extraction
PyMuPDF - PyMuPDF (current version 1.19.2) - A Python binding with support for
MuPDF, a lightweight PDF, XPS, and E-book viewer, renderer, and toolkit.

Important links

Documentation
Quick tour
Project maintainer (feel free to contact)
Future Improvements
License

Contribution
all kinds of contributions are appreciated.

Improving readability of documentation
Feature Request
Reporting bugs
Contribute code
Asking questions in discussions

Future Improvements

Web based GUI

License:

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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