There were 643 press releases posted in the last 24 hours and 298,812 in the last 365 days.

KenSci named a Cool Vendor by Gartner in Enterprise AI Governance and Ethical Response

The world’s leading research and advisory firm recognized KenSci among five providers in the category.

SEATTLE, WASHINGTON, UNITED STATES, October 29, 2019 /EINPresswire.com/ -- KenSci, an AI-based risk prediction platform for healthcare, today announced that it has been named as a Cool Vendor based on a Gartner Inc. report titled “Cool Vendors in Enterprise AI Governance and Ethical Response” by Jim Hare, Van Baker, Svetlana Sicular, Saniye Alaybeyi, Erick Brethenoux, and Alys Woodward. The report illustrated research that profiles five emerging vendors in the data and analytics market. “These vendors help organizations better govern their AI solutions, and make them more transparent and explainable,” Gartner states.

Speaking on this recognition, KenSci Co-founder & CTO, Prof. Ankur Teredesai said, “While AI is viewed as Artificial Intelligence, KenSci takes a slightly different approach of looking at it as Assistive Intelligence. We believe that AI models must be able to augment decision-making abilities of care teams to provide the best possible outcomes. We are thrilled to be chosen by Gartner as a Cool Vendor in Enterprise AI Governance and Ethical Response as KenSci believes it validates our commitment to build fair and trustable models that are able to reinforce decision processes among healthcare organizations.”

KenSci has actively invested in research to develop and build interpretable machine learning models for healthcare. KenSci’s research has been peer-reviewed and presented at leading industry forums. You can access a copy of KenSci’s research here: https://insights.kensci.com/kensci-cool-vendor

Last year, KenSci was named as an “Innovative Emerging Vendor In Value-Based Performance Management Analytics”, for having successfully combined key models such as cost accounting, revenue cycle management or predictive, progressive risk stratification with initial VBPMA features.

Gartner, Cool Vendors in Enterprise AI Governance and Ethical Response, Jim Hare, Van Baker, et al., 10 October 2019.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

About KenSci

KenSci's machine learning-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 ML platform to integrate into existing workflows. With interpretable machine learning models for healthcare, KenSci is making risk-based prediction more efficient and accountable.
KenSci was incubated at the 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.

Abhilash Kumar
KenSci
+91 9845872451
email us here
Visit us on social media:
Facebook
Twitter
LinkedIn

Legal Disclaimer:

EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.