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BioWorld - Friday, February 6, 2026
Home » Topics » Medical devices » Digital health

Digital health
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Consortium developing AI platform for improving care of severe trauma patients

Nov. 7, 2019
By Bernard Banga
PARIS – A French research consortium bringing together the firm Cap Gemini SE, the Traumabase (traumabase.eu) network, the AP-HP group of 39 teaching hospitals in the Paris region, the École Polytechnique, the National Center for Scientific Research (CNRS) and the Ecole des Hautes Etudes en Sciences Sociales (EHESS), is developing the first AI decision-making tool for managing patients with severe trauma in their first 24 hours.
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EU's new IHI program aims to 'push the boundaries,' expand innovation in health care

Nov. 7, 2019
By Nuala Moran
LONDON – The EU's next large-scale public-private research partnership in health is taking shape and due for launch at the start of 2021, succeeding the current €3.6 billion (US$4 billion) Innovative Medicines Initiative 2 (IMI2).
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Google's reported acquisition of Fitbit pits it against Apple Watch in health care arena

Nov. 5, 2019
By Meg Bryant

Tech giant Google LLC is taking aim at the Apple Watch with its plan to acquire wearables pioneer Fitbit Inc., of San Francisco, for $2.1 billion, or $7.35 per share, in an all-cash transaction expected to close sometime next year.


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Azoth and Wellmarker Bio to collaborate in AI-based cancer drug development

Nov. 4, 2019
By Jihyun Kim
HONG KONG – South Korean AI-based biotech Azoth Bio Inc., of Seongnam, Gyeonggi-do, and biopharmaceutical venture Wellmarker Bio Co. Ltd., based in Seoul, have signed a memorandum of understanding for cancer drug R&D and commercialization. Under the agreement, the two entities will use Azoth's AI-powered platform to develop Wellmarker's cancer treatment candidates.
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New device joins forces with patient network to combat TRS

Oct. 31, 2019
By David Godkin
TORONTO – Health Canada has granted a medical license to Toronto-based pharmaceuticals company Hls Therapeutics Inc. for a device that simplifies blood monitoring for patients suffering from treatment-resistant schizophrenia (TRS).
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Pilot study finds AI algorithm bests surgeons in post-op triage to the ICU

Oct. 31, 2019
By Stacy Lawrence
Deciding which patients should go into the intensive care unit (ICU) after surgery is a difficult call and typically made entirely at the surgeon's discretion. The result is that surgeons typically err on the side of caution by putting more post-operative patients in the ICU than necessary. To aid in better ICU decision-making, physicians at New York University Langone Hospital System (NYU Langone) developed a machine learning algorithm that combs through a patient's electronic medical record to identify relevant factors to determine if they needed the ICU after surgery.
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WHO looks to shape future of digital health, reduce risk of a 'negative outcome'

Oct. 30, 2019
By Nuala Moran
LONDON – The World Health Organization (WHO) aims to hit back at anti-vaccination campaigners and take a role in ensuring the safety of consumer-targeted health apps, as part of a broader push to exert more influence in shaping digital technologies to meet global public health needs.
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FDA Approved seal

Heartvista's AI-assisted cardiac MRI tool cleared

Oct. 30, 2019
By Meg Bryant
Los Altos, Calif.-based Heartvista Inc. has received the U.S. FDA's nod for its One Click autonomous MRI acquisition software for cardiac exams. The company said that One Click is the first artificial intelligence (AI)-assisted solution designed specifically with the goal of enhancing the performance and results of cardiac MRI scans.
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UCSF, Berkeley researchers develop brain bleed algorithm that bests expert radiologists

Oct. 23, 2019
By Stacy Lawrence
Radiologists review thousands of images a day. The hope is that artificial intelligence (AI) applications will become useful soon to verify diagnoses, prioritize queued images and even to offer a level of detection and measurement that aren't feasible for humans. One of the latest efforts on this front is by researchers at the University of California at San Francisco (UCSF) and the University of California at Berkeley.
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Philips, DoD develop AI-based predictive algorithm for early infection detection

Oct. 23, 2019
By Meg Bryant
Diagnosis and treatment of infections typically occurs after people exhibit obvious signs of illness, such as fever or a cough. By then, they may already have exposed others and are well on the way to developing more serious symptoms themselves. In the military, such delays can hamper medical countermeasures to contain potential outbreaks and reduce downtime among active duty personnel. Now, Amsterdam-based Royal Philips NV and the U.S. Department of Defense's Defense Threat Reduction Agency and Defense Innovations Unit have built an early warning algorithm – using artificial intelligence – to detect infection before a person shows any signs or symptoms of infection.
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