On this page we’ve collected various research papers by the Evid Science team. We were born from a scientific project sponsored by the NIH, and we continue to actively engage with the scientific community. If you want to chat about our products, AI and healthcare, or frankly, any other scientific topic, shoot us a line!
Michelson M and Reuter K. The Significant Cost of Systematic Reviews and Meta-Analyses: A Call for Greater Involvement of Machine Learning to Assess the Promise of Clinical Trials. Contemporary Clinical Trials Communications 2019; 16(1): 100443
Michelson M, Ross M & Minton, S. (2019) PNS261: How Does Machine-Learning Compare to an Incoming Medical Student in Extracting Outcomes Results from Abstracts? Value in Health. 22(2). S331. 10.1016/j.jval.2019.04.1616
Ross M, Michelson M, Tee Qiao Ying A, Ashish N, Minton N (2019) PNS265: Automated Discovery of Comparative Effectiveness Hypotheses from Medical Literature. Value in Health. 22(2). S331. 10.1016/j.jval.2019.04.1620