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
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).
The packages systematic-reviewpy and browser-automationpy are part of Thesis of Chandravesh chaudhari, Doctoral candidate at CHRIST (Deemed to be University), Bangalore, India under supervision of Dr. Geetanjali purswani.
- 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
- Saves time
- Automate monotonous tasks
- Never makes mistakes
- Provides replicable results
This project is available at PyPI. For help in installation check instructions
python3 -m pip install systematic-reviewpy
- 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.
- 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.
all kinds of contributions are appreciated.
- Improving readability of documentation
- Feature Request
- Reporting bugs
- Contribute code
- Asking questions in discussions
- Web based GUI