What I like about working on machine learning here at Elsevier is that we can combine theory with practice..— Georgios Tsatsaronis, Principal NLP Specialist
Senior Technology Researcher
If machine learning could improve the quality of science, this would have huge implications on the price and speed of drug manufacturing.
I’m a biologist by training and was brought into Elsevier to bridge the work we do in life sciences and healthcare with machine learning. One of the models I’m working on will be able to identify whether a sentence in an abstract is a result, method, hypothesis or a goal. This is important to compare papers with each other and understand the validity of the science. Non-reproducibility is a big problem, which has enormous implications for drug companies, who can’t always trust new research coming out of academia and often have to do studies all over again. If machine learning could improve the quality of science, this would have huge implications on the price and speed of drug manufacturing.
Helena Deus is Senior Technology Researcher in Elsevier’s Labs group, where she researches and creates new technologies to improve the way knowledge is conveyed.
More on Machine Learning from our tech employees
The challenge with automating healthcare technology is that the stakes are very high, since lives are on the line..— Sujit Pal, Technology Research Director
The data that we have at Elsevier is a goldmine of information for a lot of interesting and intelligent things..— Deep Kayal, Machine Learning Engineer