AI system may accelerate search for cancer discoveries
Searching through the mountains of published cancer research could be made easier for scientists, thanks to a new AI system.
The system, called LION LBD and developed by computer scientists and cancer researchers at the University of Cambridge, has been designed to assist scientists in the search for cancer-related discoveries. It is the first literature-based discovery system aimed at supporting cancer research. The results are reported in the journal Bioinformatics.
Global cancer research attracts massive amounts of funding worldwide, and the scientific literature is now so huge that researchers are struggling to keep up with it: critical hypothesis-generating evidence is now often discovered long after it was published.
Cancer is a complex class of diseases that are not completely understood and are the second-leading cause of death worldwide. Cancer development involves changes in numerous chemical and biochemical molecules, reactions and pathways, and cancer research is being conducted across a wide variety of scientific fields, which have variability in the way that they describe similar concepts.
"As a cancer researcher, even if you knew what you were looking for, there are literally thousands of papers appearing every day," said Professor Anna Korhonen, Co-Director of Cambridge's Language Technology Lab who led the development of LION LBD in collaboration with Dr Masashi Narita at Cancer Research UK Cambridge Institute and Professor Ulla Stenius at Karolinska Institutet in Sweden. "LION LBD uses AI to help scientists keep up-to-date with published discoveries in their field, but could also help them make new discoveries by combining what is already known in the literature by making connections between sources that may appear to be unrelated."
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Journal Reference:
- Sampo Pyysalo, Simon Baker, Imran Ali, Stefan Haselwimmer, Tejas Shah, Andrew Young, Yufan Guo, Johan Högberg, Ulla Stenius, Masashi Narita, Anna Korhonen. LION LBD: a Literature-Based Discovery System for Cancer Biology. Bioinformatics, 2018; DOI: 10.1093/bioinformatics/bty845