What You Should Know:
– Twin Health, a company focused on using AI digital twin technology for metabolic health, has announced a $53M investment led by Maj Invest of Denmark.
– The new funding will be…
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Copenhagen-based digital health company specializing in chronic disease management, Dawn Health secured $13 million (€11.5 million) from existing investors Chr. Augustinus Fabrikker, the export and investment fund of Denmark (EIFO) and Trifork. WHAT IT DOES
Dawn…
Denmark-based Teton, a company that offers an AI companion to help nurses monitor patients and optimize workflow, announced it created a real-time, live 3D reconstruction of a hospital room using Gefion, Denmark’s national supercomputer.The…
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Although promising, the clinical impact of video conferencing between primary and secondary care specialists lacks trial evidence. We conducted a two-arm RCT (clinicaltrials.gov: NCT05268081) to evaluate whether four video conferences over 12 months between…
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We interviewed four nursing professionals from Denmark, Spain, Sweden, and France to better understand the current and future challenges in nursing, the role of technology in supporting nurses and their patients, and how the…
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The UK healthcare sector is at risk of falling behind other European countries in adopting AI, according to a pan-European study.
The report, produced by healthcare AI research and development company Corti and YouGov, shows…
Chicago-based Sibel Health, a medical technology company, has been picked by the capital region of Denmark for a long-term partnership in conjunction with Dräger, a medical safety technology company, to deploy advanced continuous monitoring…
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Introduction
Artificial intelligence (AI) is transforming breast cancer detection by enhancing early diagnosis and alleviating radiologist workload, essential for improving patient outcomes and screening efficiency. A recent study, conducted by researchers from Norway and Denmark,…
ImpriMed, a precision medicine company, announced that it has expanded its services to include human oncology.The aim is to provide drug-response predictions for routine blood cancers such as newly diagnosed multiple myeloma and acute…
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We aimed to identify and characterise behavioural profiles in patients at high risk of SCD, by using deep representation learning of day-to-day behavioural recordings. We present a pipeline that employed unsupervised clustering on low-dimensional…
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