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Study on AI in Healthcare Dissects Digital Health Technologies in Europe

This study analyses the EU digital health market and economic impact of digital health technologies, including AI-enabled solutions.

This area is a priority workstream for the AI Office, reflecting its importance for AI innovation and competitiveness. The study Observatory for digital health technologies in Europe was commissioned by the Directorate-General for Communications Networks, Content and Technology (DG CONNECT).

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AI Helps to Evaluate Skin Lesions in Rare Disease More Accurately

There is a promising new drug for the rare disease mastocytosis, which is associated with skin lesions, among other things. Researchers at the University of Basel have now been able to use artificial intelligence (AI) to quantitatively measure for the first time the extent to which it reduces skin lesions.

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Using AI to Improve Standard-of-Care Cardiac Imaging

Heart disease is the leading cause of adult death worldwide, making cardiovascular disease diagnosis and management a global health priority. An echocardiogram, or cardiac ultrasound, is one of the most commonly used imaging tools employed by physicians to diagnose a variety of heart diseases and conditions. 

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Orchestrated Multi-Agent AI Systems Outperforms Single Agents in Health Care

As artificial intelligence (AI) becomes more common in health care, from managing records to assisting with medication decisions, researchers at the Icahn School of Medicine at Mount Sinai are asking an important question: How well does AI hold up when the workload gets intense at health system scale?

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How AI is Integrated into Clinical Workflow Lowers Medical Liability Perception

Artificial intelligence (AI) is changing the field and practice of medicine, including legal liability and the perception of who is at fault when a patient experiences harm.

“AI holds promise to improve the quality and safety of health care and to reduce errors and patient harm, but the risk of legal liability is a potential barrier for investment and development of this technology as well as the quality of care,” said Michael Bruno, professor of radiology and of medicine at Penn State College of Medicine.

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Philips Expands Digital Pathology Portfolio with Cloud-Enabled Philips IntelliSite Pathology Solution on HealthSuite

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, announced the expansion of its digital pathology portfolio with new cloud-enabled capabilities designed to help healthcare organizations scale digital diagnostics, improve productivity, and advance their transformation to fully digital workflows.

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Predicting Brain Health with a Smartwatch

Can smartphones or smartwatches help detect early signs of neurological or mental illness? Researchers at the University of Geneva (UNIGE) monitored a group of participants wearing connected devices, and used artificial intelligence to analyse data such as heart rate, physical activity, sleep and air pollution. Their findings show that connected devices can accurately predict emotional and cognitive fluctuations, opening new avenues for the early detection of changes in brain health.

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AI can Predict Risk of Serious Heart Disease from Mammograms

The risk of serious or fatal heart disease can be predicted with artificial intelligence (AI) analysis of mammograms, according to research published in the European Heart Journal.

The study shows that AI can be used to assess the build-up of calcium deposits in the arteries of the breast from the standard X-ray mammography scans that are currently used in routine breast cancer screening.

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Nearly Half of UK Adults Happy to Use ChatGPT as a Counsellor

More than 4 in 10 adults in the UK are happy to use ChatGPT for their mental health support, new research suggests.

The study, led by Bournemouth University surveyed nearly 31,000 adults in 35 countries about their use of Artificial Intelligence (AI) large language models such as ChatGPT. The research also discovered that:

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Automated CT Scan Analysis could Fast-Track Clinical Assessments

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease. Scientists used their tool, named Merlin, to assess 3D abdominal computed tomography (CT) scans, accomplishing tasks as simple as identifying anatomical features to as complex as predicting disease onset years in advance.

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