annalise.ai expands to India
AI radiology company annalise.ai is continuing its global expansion with the opening of its first location in India.
Its entry into one of the fastest-growing medical device markets in the world aligns with its fast-paced growth trajectory while increasing its visibility and capabilities in other new markets such as the United States, the United Kingdom, Europe, and Asia.
Based on a media release, Annalise India Centre in Chennai will focus on the development and marketing of new products.
CEO Lakshmi Gudapakkam also said there is an opportunity to “make use of the diverse talent pool that makes India a technological hub and accelerate the development of new AI applications.” The company is looking to hire talents in product development, including software engineers, product managers and regulatory, as well as expand its commercial and business services teams.
Alcidion, Coviu announces integration for real-time RPM
Health technology companies Alcidion and Coviu have teamed up to offer a new real-time remote patient monitoring solution.
Alcidion’s Miya Care app is now integrated into Coviu’s platform, allowing care teams to set up tasks for patients during their recovery at home. Health practitioners can then check up on their patients through video conferencing, staying on top of their conditions over time and preventing escalations.
This integration also enables Coviu to alert clinicians whenever it finds abnormalities in the vital signs data collected through the Miya Care app.
Beamtree names AI data analytics research head
Beamtree has appointed Dr Ben Hachey of the University of Sydney to the position of associate professor in clinical informatics, leading research projects in applied AI for healthcare data in the University of Sydney’s Faculty of Medicine and Health.
Dr Hachey has over 20 years of academic and industry experience in AI and data science and over 60 research outputs which are mostly on AI in health.
According to a media release, he will spearhead research efforts across several areas, including:
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new methods for making patient data available to support clinical decision support tools;
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better mapping patient data to assist in research and clinical surveillance activities; and
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applying machine learning and other data science models to patient data.
