Huge NHS Cloud Deals Mean Tough Questions: Here's What Imaging Tech Suppliers Must Prove

Opinion Article by Chris Scarisbrick, Deputy Managing Director, Sectra.
The largest public cloud projects to ever take place within the NHS are beginning. Regional procurements for public cloud hosted diagnostic imaging solutions have recently seen the earliest of adopters go-live.

Now, a tsunami is set to follow, with projects involving vast amounts of data needed for the care of millions of patients, soon to become commonplace.

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Will Generative AI Change the Way Universities Communicate?

Since the launch of ChatGPT 3 in November 2022, we've been abuzz with talk of artificial intelligence: is it an unprecedented opportunity, or will it rob everyone of jobs and creativity? As we debate on social media (and perhaps use ChatGPT almost daily), generative AIs have also entered the arena of university communication. These tools - based on "Large Language Models" that were optimized for interactive communication - can indeed support, expand, and innovate university communication offerings.

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Comprehensive Bibliographic Dataset Advances Health AI Research

A groundbreaking study published in Health Data Science, a Science Partner Journal, introduces a curated bibliographic dataset that aims to revolutionize the landscape of Health Artificial Intelligence (AI) research. Led by Xuanyu Shi and Jian Du from Peking University, this dataset integrates a vast array of Health AI-related documents, offering an invaluable resource for researchers, policymakers, and practitioners.

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Philips ePatch and AI Analytics Platform Rolled Out to 14 Hospitals Across Spain to Monitor Heart Patients

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, announced the successful nationwide rollout of its ambulatory cardiac monitoring service in Spain using its unique wearable ePatch paired with its AI-driven Cardiologs analytics platform. 14 Spanish healthcare providers across the country are now using the company's ePatch extended wear Holter monitors to detect life-threatening heart arrhythmias such as atrial fibrillation (AF).

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AI can Help Improve Emergency Room Admission Decisions

Generative artificial intelligence (AI), such as GPT-4, can help predict whether an emergency room patient needs to be admitted to the hospital even with only minimal training on a limited number of records, according to investigators at the Icahn School of Medicine at Mount Sinai. Details of the research were published in the online issue of the Journal of the American Medical Informatics Association.

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New AI Algorithm may Improve Autoimmune Disease Prediction and Therapies

A new advanced artificial intelligence (AI) algorithm may lead to better - and earlier - predictions and novel therapies for autoimmune diseases, which involve the immune system mistakenly attacking their body’s own healthy cells and tissues. The algorithm digs into the genetic code underlying the conditions to more accurately model how genes associated with specific autoimmune diseases are expressed and regulated and to identify additional genes of risk.

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ChatGPT Extracts Data for Ischaemic Stroke Almost Perfectly

In an ischaemic stroke, an artery in the brain is blocked by blood clots and the brain cells can no longer be supplied with blood as a result. Doctors must therefore act quickly and unblock the artery with the help of catheters. During the so-called mechanical thrombectomy, a lot of data has to be recorded and then transferred to various registers.

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Is 'Smart Health Tech' Solving the Right Problems for the NHS?

Opinion Article by Dr. Paul Deffley, Chief Medical Officer, Alcidion.
Where would you position the NHS in relation to other countries, when it comes to the adoption of innovative technologies to support patient care?

Recent research from Newsweek and Statista, which ranked the world’s top 'smart hospitals', placed its first NHS trust at position 72 on the list.

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AI Tool to Improve Heart Failure Care

UVA Health researchers have developed a powerful new risk assessment tool for predicting outcomes in heart failure patients. The researchers have made the tool publicly available for free to clinicians.

The new tool improves on existing risk assessment tools for heart failure by harnessing the power of machine learning (ML) and artificial intelligence (AI) to determine patient-specific risks of developing unfavorable outcomes with heart failure.

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Why Standards are Key to Building Trust in AI

Opinion Article by Dean Mawson, Clinical Director and Founder, DPM Digital Health Consultancy.
There's considerable interest in the potential uses of AI in healthcare at the moment; but there is also concern about the possible risks that it could pose.

Challenges include questions about data privacy and algorithmic bias, how we can make sure that AI tools are subject to robust validation and testing processes, and how to make sure they are used safely in a clinical setting.

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