The business idea of Research Screener is a web application that applies machine learning techniques to semi-automate research article screening.
Research Screener was the winner of the inaugural EduGrowth LaunchPad Business Start EdTech business plan competition. The submission, interview and presentation by Leo Ng as team leader impressed the judging panel consisting of Dan Ingvarson, Carlos Schafer and Pauline Farrell. Who commented that this business idea is truly innovative with the potential of saving significant research time.
Research Screener is the work of Dr Leo Ng, researcher and research educator, Mr Peter Edwards, computer programmer, and Dr Kevin Chai, data scientist, all from Curtin University.
Their business plan submission highlighted that more than 65,000 research students in Australian Universities have the task of finding research papers relevant to their project. With individuals spending hundreds of hours often reading irrelevant articles.
The innovative business solution to this problem is a Web application that applies machine learning techniques (natural language processing) to semi-automate research article screening.
It works by users uploading titles and abstracts of research articles from existing library databases to the Web app then manually screening a portion of these articles (e.g. 100). The Web app actively learns what articles are, or, are not, relevant to the research based on the users screening.
The Web app then screens the title and abstracts of 2,000 – 100,000 articles in minutes rather than researchers spending months and identifies those articles that are deemed relevant or irrelevant.
No existing products use machine learning techniques to automate the screening of research articles.
As winner of the EduGrowth Business Start Business Plan Competition 2018, Research Screener was awarded a cash prize of $5,000 as well as mentoring sessions from an EdTech Entrepreneur and other products and services to help advance this innovative EdTech business.
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