Prepare.AI Conference – Growing at UNCOMN

At UNCOMN, we challenge our team members to grow both personally and professionally. “Growing at UNCOMN” provides a snapshot of just some of the professional development our people take part in. We sent a couple of our Data Scientists to learn about how artificial intelligence is changing the world of business.

Prepare.AI Conference

In April, we had the opportunity to attend the Prepare.AI conference. is a nonprofit, St. Louis organization created to increase collaboration around, and awareness of, AI technology for individuals, companies, and communities. We attended several sessions ranging from topics on how AI is being used in the healthcare field to how it is being used to improve business practices and advertising. Conference

Although AI has various applications, this conference focuses on data practices, which includes machine learning and probabilistic methods. Machine learning is the automated process of model building. It is a collection of algorithms designed to find patterns and relationships in a provided training data set. A test data set, which was not included in the training data set, is then used to assess how well the algorithm models the data. While machine learning is not always appropriate when trying to obtain meaning from data, it is a very interesting and exciting advancement in data exploration. It has the potential to provide insight not previously available in traditional statistical methods.


The conference also highlights how St. Louis is a focal point for AI integration in research and business practices. We heard interesting presentations from WashU, Evolve24, 1904Labs, Mercy Virtual, Panera, Label Insight, Maritz Motivation Solutions, Health Literacy Media, Big Squid,, and NBS Consulting. All of these businesses are based in St. Louis and are interested in not only bettering their business through data AI, but they are also growing a strong community of scientists in this area.


Our favorite presentation of the day was Allocating Scarce Societal Resources Based on Predictions of Outcomes. This presentation focused on the allocation of scarce resources (ex: organ transplantation, resources for homeless people). The speaker, Dr. Sanmay Das, an Associate Professor at the McKelvey School for Engineering at WashU, spoke about how he, with his colleagues and students, are using machine learning to optimize patient outcomes for kidney transplants.

As he explained, most people who donate a kidney do so because they have a loved one who needs a kidney. In the event that they are not a match, they are often open to the idea of doing an exchange. For example, patient A and patient B both have a loved one who is willing to donate but for which they are not a match. So, patient A’s loved one donates to patient B and vice versa. Dr. Das and his colleagues wondered, could there be better outcomes for all involved if everyone who is willing to donate goes in a pool, even if they match with their loved one. Their research, largely based on machine learning, shows that pooling all donated kidney’s would allow for better patient matches overall. There would be an increased likelihood of positive outcomes and those positive outcomes would be even better than without pooling. There would be an increase not only in the number of positive outcomes but also in the quality of the positive outcomes. This topic was enlightening about how machine learning is being used to help cultivate beauty in our community.


We appreciated this invaluable opportunity to network and learn more about data AI in the St. Louis area. We left the conference feeling energized and excited to help UNCOMN grow in this field of innovative technology.

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