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WellAI Data Scientists to Present Latest Research on ML in Healthcare and Finance

The Online Event is Jointly Organized with the Society of Quantitative Analysts

WellAI data scientists Daniel Satchkov and Sergei Polevikov will present their most recent research entitled “Reading 25 Million Studies in Seconds: Implications for Fighting COVID-19 and Managing a Portfolio” at a free webinar on August 25, 2020. The webinar will take place from 12pm to 1pm EST, and is jointly organized by the Society of Quantitative Analysts (SQA) and WellAI.  Discussion will be partly based on a study “Artificial Intelligence-powered search tools and resources in the fight against COVID-19” published in the Journal of the International Federation of Clinical Chemistry and Laboratory Medicine in June 2020, and is currently available through the PubMed database of the National Institutes of Health (NIH).

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Sergei Polevikov, CEO of WellAI and a board director at SQA, explained: “We wanted to share our unique experience as we believe our work is relevant to both medical researchers and finance professionals.  WellAI data scientists had built a free COVID-19 analytical tool for medical researchers around the world in early April 2020, to help fight the pandemic.  As some of us had also had previous experience as data scientists in the finance industry, we found some interesting similarities and differences in a way one applies machine learning algorithms in healthcare versus applying those in finance.  What better place to share this knowledge than the SQA – one of the most recognized organization in the United States among the quantitative investment professionals?”

“We are thrilled to host this webinar,” says Lilian Quah, CFA, the President of the SQA. “We are grateful to Daniel, Sergei, and their team at WellAI for their contributions to the global fight against COVID-19. When they approached us about a seminar contrasting the application of machine learning techniques to two different fields – healthcare and finance – we were immediately intrigued. The SQA has a long history of featuring exploratory topics outside of those directly related to quantitative investing. We have always believed in the power of learning from other domains.”

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Natural language processing (NLP) models, or neural network models of language, can be used to significantly improve analytics in various fields, including healthcare and finance.  WellAI team has trained language neural networks on the large sets of medical studies, such as 25 million+ articles available on PubMed, or almost 200,000 articles on the novel coronavirus (COVID-19) available through the CORD-19 dataset. WellAI COVID-19 model allows researchers to quickly elucidate relationships between thousands of concepts from millions of studies without having to fit any closed form statistical models or distributions. Neural networks of language give us two things that we are missing in finance: virtually unlimited amount of data and mathematical model that reflects the complexity of joint distributions. They contain everything we need in order to estimate relationships between concepts or variables.

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