GitHub - xmkrohannon/Deep-Learning: Per the 2018 STM Report there are over 33,100 peer-reviewed journals in print, each with their own specific research area and specifications. One heavily weighted metric used by journals is the impact factor, measured by the number of times an article is published within a set duration of its publish date, typically 6 months. As a result, a tool to predict a proposed article’s impact factor is desired, as a means to aid in researchers in selecting journals to submit their article to. Here we present, DeepImpact a deep learning model that takes an article’s abstract, as well as the primary author’s institutional association as features to predict the likely impact factor of that particular work, with 90% accuracy.

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Per the 2018 STM Report there are over 33,100 peer-reviewed journals in print, each with their own specific research area and specifications. One heavily weighted metric used by journals is the impact factor, measured by the number of times an article is published within a set duration of its publish date, typically 6 months. As a result, a tool…

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Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
Article_Parser.py		Article_Parser.py
DeepImpact_Report.docx		DeepImpact_Report.docx
Deep_Learning_Report.docx		Deep_Learning_Report.docx
Group1_DL_scenario1.ipynb		Group1_DL_scenario1.ipynb
Group1_DL_scenario2.ipynb		Group1_DL_scenario2.ipynb
Pasre_Articles.sh		Pasre_Articles.sh
Pubmed_Data_Download.sh		Pubmed_Data_Download.sh