Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV-2 pandemic. In this work we propose a novel machine learning based approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies aiming to slow down the rapid spread of COVID-19.

Information contained on this page is provided by an independent third-party content provider. If you are affiliated with this page and would like it removed please contact pressreleases@franklyinc.com Cogitativo, Inc., the first-to-market machine learning and data-science-as-a-service company for healthcare organizations, announced today the closing of a $5 million Series A funding round. The strategic investment by HCSC Ventures, Inc., a wholly-owned subsidiary of Health Care Service Corporation which specializes in investments in innovative health care companies, will support the product-line expansion for anomaly detection and real-time operational decision support solutions for healthcare payers. Cogitativo brings a new scientific paradigm to the rapidly growing market for healthcare performance improvements by enabling payers and providers to challenge system complexity through Cogitativo's machine learning platform. Cogitativo has more than tripled in size over the past two years while introducing new disruptive, machine learning products in areas of payment integrity and anomaly detection.

BBN's project in knowledge representation for natural language understanding is developing techniques for computer assistance to decision maker who is collecting information about and making choices in a complex situation. In particular, we are designing a system for natural language control of an intelligent graphics display. This system is intended for use in situation assessment and information management.