With a disease as new and fast-moving as COVID-19, it can be difficult for providers in far-flung places to keep up with the latest research and possible solutions as they work to combat the disease in their locales.
To give them a hand, software giant SAS has released its COVID-19 Scientific Literature Search and Text Analysis, a free visual text analysis environment AI and machine learning to quickly search tens of thousands of research articles on COVID-19 and deliver potentially lifesaving answers to providers.
In just a few, short months, the company says, research groups have gathered and released to the public more than 50,000 full-text scientific research articles on COVID-19 and other coronaviruses through the COVID-19 Open Research Dataset. These articles include studies on treatment effectiveness, vaccine development, mitigation efforts, genetic analysis, economic impact and more.
"Effectively mining unstructured text from scientific literature can take teams of people, many needing deep subject matter expertise, and substantial amounts of time to effectively categorize and determine relevancy," said Mark R. Cullen, MD, Professor of Medicine at Stanford University and Chair of the COVID-19 Research Database Scientific Steering Committee. "SAS has put forth a solution that expedites this process and enables researchers across the globe to support their COVID-19 related efforts such as understanding the effectiveness of treatments or better understanding genetic variables in COVID mutations.”
Drawing on AI, natural language processing, linguistic rules and sophisticated modeling techniques, SAS' COVID-19 Scientific Literature Search and Text Analysis environment enables quick and intelligent extraction of relevant text and numerical data from CORD-19.
With SAS' new visual text analysis environment, users can interactively explore relevant research on coronavirus topics such as incubation period, genetic variations, risk assessment and more. They can also visualize extracted keywords and summarized quantitative data, quickly identify co-citations and the authority of papers using network analysis visualization, and search for key terms in free text.
"The COVID-19 pandemic has led to an explosion of medical and scientific research, far more than any one person can meaningfully consume," said Jeffrey Engel, MD, of the Council of State and Territorial Epidemiologists. "The SAS environment, using its advanced analytic and AI capabilities, provides global researchers, public policy analysts, epidemiologists, healthcare providers and academia the ability to focus on topics that are relevant, sources that are authoritative, and findings that are impactful in their efforts to stop COVID-19.”
The company has also released the COVID-19 Epidemiological Scenario Analysis, an interactive environment that builds on medical resource optimization models created jointly with Cleveland Clinic. The models run different virus-projection scenarios to predict the impact of a disease outbreak and quantify the effectiveness of public health mitigation strategies.