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Using Deep Learning for Precision Cancer Therapy

Altuna Akalin and his team at the Max Delbrück Center have developed a new tool to more precisely guide cancer treatment. Described in a paper published in Nature Communications, the tool, called Flexynesis, uses deep neural networks and evaluates multi modal data.

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.

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).

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.

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.

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.

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.

DIGITAL HEALTH NEWS

Using Deep Learning for Precision Cancer Therapy

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

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

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

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

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

New Training Year Starts at Siemens Healthineers

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