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Study Sheds Light on Hurdles Faced in Transforming NHS Healthcare with AI

Implementing artificial intelligence (AI) into NHS hospitals is far harder than initially anticipated, with complications around governance, contracts, data collection, harmonisation with old IT systems, finding the right AI tools and staff training, finds a major new UK study led by UCL researchers.

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Digital ECGs at Barts Health: A High-Impact Win for NHS Digitisation

Opinion Article by Dr Krishnaraj Sinhji Rathod, consultant in interventional cardiology, Barts Health NHS Trust.
Picture the moment. A patient in an ambulance, enroute to hospital with new chest pain. Paramedics understandably suspect a possible heart attack having carried out an electrocardiogram (ECG).

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Study Used AI Models to Improve Prediction of Chronic Kidney Disease Progression

Chronic kidney disease (CKD) is a complex condition marked by a gradual decline in kidney function, which can ultimately progress to end-stage renal disease (ESRD). Globally, the prevalence of the CKD ranges from 8% to 16%, with about 5% to 10% of those diagnosed eventually reaching ESRD, making it a major public health challenge.

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New AI Approach Paves Way for Smarter T-cell Immunotherapy and Vaccine Development

Researchers have harnessed the power of artificial intelligence (AI) to tackle one of the most complex challenges in immunology: predicting how T cells recognize and respond to specific peptide antigens. Using AlphaFold 3 (AF3), a AI/ML model, designed for protein structure prediction, the team demonstrated a novel approach to model T cell receptor–peptide/major histocompatibility complex (TCR-pMHC) interactions with growing accuracy.

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New AI Tool Addresses Accuracy and Fairness in Data to Improve Health Algorithms

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms - addressing a critical issue that can affect diagnostic accuracy and treatment decisions. The findings were published in the September 4 online issue of the Journal of Medical Internet Research.

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New Training Year Starts at Siemens Healthineers

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens Healthineers. Training in technical professions predominates, followed by IT and commercial professions. For Siemens Healthineers, in-house training is an important factor in meeting the high demand for qualified junior staff and thus developing the company in the long term.

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Global Study Reveals How Patients View Medical AI

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich (TUM) has investigated this for the first time in a large study spanning six continents. The central finding: the worse people rate their own health, the more likely they are to reject the use of AI.

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Alcidion Grows Top Talent in the UK, with New MD, CCIO and CRO Appointments

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the UK Managing Director, with Tracy McClelland and Darren Ransley joining as global Chief Clinical Information Officer (CCIO) and Chief Revenue Officer (UK), respectively.

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Are You Eligible for a Clinical Trial? ChatGPT can Find Out

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates.

Researchers at UT Southwestern Medical Centre used ChatGPT to assess whether patients were eligible to take part in clinical trials and were able to identify suitable candidates within minutes.

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International Study Reveals Sex and Age Biases in AI Models for Skin Disease Diagnosis

An international research team led by Assistant Professor Zhiyu Wan from ShanghaiTech University has recently published groundbreaking findings in the journal Health Data Science, highlighting biases in multimodal large language models (LLMs) such as ChatGPT-4 and LLaVA in diagnosing skin diseases from medical images.

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