Machine Learning Toolkit for Grey Literature Screening

VISIMO’s ML Toolkit for Grey Literature Screening will reduce bias in, and improve accuracy of, systematic reviews (SRs) for chemical risk assessment. Grey literature is notoriously difficult to screen and tag, and despite its importance, researchers often exclude grey literature from their SRs due to necessity. VISIMO’s Toolkit will enable researchers to filter full documents of all types and formats, identify relationships between documents, determine source relevance, and perform improved meta-tagging. These capabilities will enable researchers to identify relevant grey sources and thus improve the quality of their SRs. While other software addresses literature screening in a generalized manner, to our knowledge, VISIMO’s solution is the only tool designed for literature screening with the challenges of grey literature in mind. While VISIMO’s solution is designed to meet EPA needs, our tool can be utilized by risk assessors and scientists, researchers, librarians, and industry leaders within a variety of disciplines, including environmental science and beyond. VISIMO’s Toolkit will increase the accuracy of SRs for chemical risk assessment, and thus result in significant positive environmental impact through supporting risk reduction of various chemicals.