The Allen Institute of Artificial Intelligence (AI2) Adds Over 30 Million Biomedical Papers to Semantic Scholar to Help the Medical Community Fight Information Overload and Save Lives

AI2 introduces scientific knowledge graph linking biomedical terms, definitions, and current research papers

SEATTLE--()--The Allen Institute for Artificial Intelligence (AI2) today announced its AI-based academic search engine, Semantic Scholar, has made significant progress with the addition of tens-of-millions of biomedical papers. Semantic Scholar enables deep information extraction and entity linking to create a scientific knowledge graph out of the insights buried in millions of documents. Semantic Scholar now covers neuroscience, computer science and biomedical papers and is tracking towards a million users per month.

With the addition of biomedical journals and papers, Semantic Scholar can have an immediate impact on those who are in the midst of critical scientific breakthroughs to treat the most threatening diseases. By relying less on manually annotated data and instead creating algorithms that delve into the content of the articles, AI2 is able to extract information that makes user queries far more accurate and efficient.

“We believe the greatest impact AI can have is in analyzing, understanding, and surfacing academic, scientific, and medical research - the most important information on the planet,” said Marie Hagman, Senior Product Manager at AI2. “In the medical field, the common term ‘second opinion’ speaks to the fact that two domain experts in the same field of study may carry different opinions of symptoms, diseases, treatments and more. There is some benefit in this, but when it comes to our most debilitating and deadly diseases, the most cutting-edge research and treatments are required and not always surfaced. We want to use AI and the Internet to its full potential to save lives.”

In a commentary published in the journal Nature, AI2 CEO Oren Etzioni wrote,” Massive bodies of text such as the corpus of web pages are highly redundant: many assertions are expressed multiple times in different ways. When a system extracts the same assertion many times from distinct, independently authored sentences, the chance that the inferred meaning is sound goes up exponentially.

“Semantic Scholar is more reflective of the way I think about a topic and the way I want to learn about and explore a topic,” said Samuel Du, a researcher at Children’s Hospital. Other academic search engines can be helpful if you know exactly what you are looking for, but if you don’t it’s hard to tell what’s important and what’s not."

Earlier this year, Semantic Scholar brought together Microsoft, Google and Baidu to contribute resources for the Open Academic Search (OAS), an extension of Semantic Scholar. Together, AI2 hopes to eventually work in tandem with the publishing of papers, allowing researchers to spend more time creating and less time tabulating.

About AI2

AI2 was founded in 2014 with the singular focus of conducting high-impact research and engineering in the field of artificial intelligence, all for the common good. AI2 is the creation of Paul Allen, Microsoft cofounder, and is led by Dr. Oren Etzioni, a renowned researcher in the field of AI. AI2 employs more than 75 top-notch researchers and engineers, attracting individuals of varied interests and backgrounds from across the globe. AI2 prides itself on the diversity and collaboration of this team, and takes a results-oriented approach to complex challenges in AI.

Contacts

for AI2
Jessica Piha
or
John O’Brien
press@strangebrewstrategies.com

Contacts

for AI2
Jessica Piha
or
John O’Brien
press@strangebrewstrategies.com