Sensyne is a healthcare technology company that uses advanced algorithms and Artificial Intelligence (AI) techniques to analyze anonymized patient data, helping healthcare professionals to perform better diagnoses and offer targeted treatments, while academic and industrial partners use the companyu2019s proprietary technology to undertake groundbreaking research and development.
The company was founded in 2018 by Lord Paul Drayson, who had previously been the Minister of Science and Innovation in the UK government and had developed a keen interest in healthcare technology.
In 2019, Sensyne went public and joined the AIM market of the London Stock Exchange, raising u00a360m through its initial public offering.
Since then, the company has established partnerships with several leading NHS trusts in the UK, as well as numerous academic institutions and pharmaceutical companies.
In 2020, Sensyne entered the US market by acquiring the clinical AI company, DigiBiomarkers.
In 2021, Sensyne announced a partnership with the University of Oxford to develop and deploy algorithms that can analyze real-world data from patients with COVID-19, with the goal of improving outcomes for those affected by the virus.
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Sensyne is a healthcare technology company that uses advanced algorithms and Artificial Intelligence (AI) techniques to analyze anonymized patient data, helping healthcare professionals to perform better diagnoses and offer targeted treatments.
Sensyne has partnerships with several leading NHS trusts in the UK, as well as numerous academic institutions and pharmaceutical companies.
SYNE-COV is an artificial intelligence-powered platform that analyzes real-world patient data to identify risk factors and improve outcomes for those affected by COVID-19.
GDm-Health is an app-based digital therapeutic that helps pregnant women with gestational diabetes manage their condition through remote monitoring and personalized guidance.
SENSE is an artificial intelligence-powered clinical decision support system that uses machine learning algorithms to identify personalized treatment options for patients with diabetes.
