KenSci's research chosen as Best in Category at AIMed North America 2018

SEATTLE, Jan. 16, 2019 /PRNewswire/ -- KenSci, a machine learning and artificial intelligence powered risk prediction platform for healthcare, was awarded the Best in Category by AIMed North America for the presentation of its research. The research abstract was presented at the main stage of AIMed North America in California on December 14, 2018, along with six other finalists.

The paper titled "Needle in a Haystack: Using Machine Learning to identify opportunities for pharmacy optimization," explores a novel machine learning approach to identify opportunities for pharmacy optimization at a large US health system. By using trend detection and clustering KenSci was able to help the health system reduce pharmacy costs and improve quality.

"We are honored to be selected as the Best in Category award winner at AIMed. Our main goal in creating this framework was to bring a large impact in the overall costs associated with healthcare," said Ankur Teredesai, Co-founder and CTO, KenSci, "Only 1% of all commercial AI use-cases rely on unsupervised learning. Notably at KenSci for this work we were able to operationalize an unsupervised learning to discover clusters, learn and revise incrementally, and help the health system improve both - their care quality and save costs at the same time."

"KenSci, with its predictive analytics leading to a pharmacy optimization project, took best in category prize at our very competitive AIMed abstract competition!" said Dr. Anthony Chang, Founder, AIMed and Chief Artificial Intelligence Officer Children's Hospital of Orange County (CHOC).

Incubated at the University of Washington Tacoma, KenSci has published over 30 academic papers that are peer reviewed and have been showcased across leading industry events. In early 2018, KenSci's paper titled "Death Vs Data Science" was chosen as the winner of the prestigious Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18).

About KenSci: 

KenSci's machine learning and AI powered risk prediction platform helps healthcare providers and payers intervene early by identifying clinical, financial and operational risk to save costs and lives. KenSci's platform is engineered to ingest, transform and integrate healthcare data across clinical, claims, and patient generated sources. A library of pre-built models and modular solutions allows KenSci's machine learning platform to integrate into existing workflows. With Explainable AI models for healthcare, KenSci is making risk based prediction more efficient and accountable.

KenSci was incubated at University of Washington's Center for Data Science at UW Tacoma and designed on the cloud with help from Microsoft's Azure4Research grant program. KenSci is headquartered in Seattle, with offices in Singapore and Hyderabad. For more information, visit www.kensci.com.

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