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!

Journal Articles:

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

Del Fiol G, Michelson M, Iorio A, Cotoi C, Haynes RB. A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study. J Med Internet Res 2018;20(6):e10281

Conference Abstracts:

Michelson M, Ross M & Minton, S. (2019) AI2: Leveraging Machine-Assistance to Replicate a Systematic Review. Value in Health. 22(2). S34. 10.1016/j.jval.2019.04.006.

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