Incorporating machine-learning tools into data analysis can accelerate discovery and free up valuable time.<\/p>\n
Artificial-intelligence programs can speed up monotonous tasks in research \u2014 and the learning curve is not too steep.<\/p>\n
Image-analysis tools can do amazing things. Yet despite their power, Fernanda Garcia Fossa was frustrated. A biology PhD student at the State University of Campinas, Brazil, Garcia Fossa specializes in nanotoxicology. Image-based profiling of human cells is a core part of her research. But when she started out, the process was slow and error-prone.<\/p>\n
\u201cI spent a lot of my time analysing my images individually by hand, looking for differences and patterns,\u201d Garcia Fossa explains. She was looking for evidence of the subtle effects of silver nanoparticles on liver cells. But the number of hours it took to compare scanned images of each cell one by one was overwhelming, she says. \u201cI thought, there has to be a faster way to do this.\u201d<\/p>\n
Trawling online biology forums, she stumbled on CellProfiler, an image-analysis tool based on artificial intelligence (AI) developed at the Broad Institute of MIT and Harvard in Cambridge, Massachusetts. Within hours, she had identified an algorithm tailored to her needs, which she used to analyse her images automatically. \u201cIt was exciting,\u201d she says. \u201cSuddenly, I found I had more time to do other tasks related to my research, because the program was analysing all my images for me.\u201d<\/p>\n