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Green AI in radiology: The carbon footprint of our models and ways to reduce it

Starting this month, the UK’s National Health Service (NHS) requires all suppliers of new high-value ... Continue reading...

A defining year in the Aidence journey: Our 2022 highlights

This year, it became apparent that our bold ambitions can come true. Backed by a ... Continue reading...

Catching up with lung cancer: AI and the post-pandemic imaging backlog

Covid-19 has brought profound changes to lung cancer care. In combination with staff shortages, it ... Continue reading...

The puzzling case of autonomous AI in medical imaging

“Welcome to the era of autonomous AI in medical imaging,” read an announcement from an ... Continue reading...

From AI model to software medical device: Why the algorithm is only a fraction of the work

A good rule of thumb we can confirm from our own experience developing AI medical ... Continue reading...

Why cloud computing is the best option for hospitals adopting AI

“Cloud computing” is something of a misnomer – a term wrongly applied due to a ... Continue reading...

The partnerships, upgrades, articles and events that defined 2021

It was the best of times; it was the worst of times, one could say, ... Continue reading...

Bias in medical imaging AI: Checkpoints and mitigation

This year, the medical imaging AI industry was shaken by research showing that an AI ... Continue reading...

Lessons learnt supporting the NHS England Targeted Lung Health Checks

Lung cancer is a devastating illness. It kills one person every 30 seconds and costs ... Continue reading...

Quality improvement in theory and practice: Guiding principles and a real-world incident fix

As a clinician, I was always interested in quality improvement. I enjoyed the logic of ... Continue reading...

In a race between AI algorithms, the best software will win

The inspiration for this article came from a tweet by Dr Amine Korchi, neuroradiologist and ... Continue reading...

A new era of post-market surveillance for AI medical solutions

Medical device manufacturers often consider post-market surveillance (PMS) as an activity conducted by their regulatory ... Continue reading...

Making a case for buying medical imaging AI: How to define the return on investment 

There have been many claims about technologies making healthcare better or more affordable. Artificial intelligence ... Continue reading...

The (not-so-distant) future of AI in healthcare

There have been many claims about technologies making healthcare better or more affordable. Artificial intelligence ... Continue reading...

Where does medical imaging AI have the most impact today?

There have been many claims about technologies making healthcare better or more affordable. Artificial intelligence ... Continue reading...

The five-step guide to AI adoption in clinical practice

The adoption of medical imaging AI is about getting your hospital or screening programme ready ... Continue reading...

The roadmap to a safe and sustainable AI medical solution, during and beyond covid-19

The covid-19 pandemic demands urgent action to manage the influx of patients. For AI companies, ... Continue reading...

Workflow integration is the game-changer for medical imaging AI

The potential extra burden of AI Medical imaging technology is increasingly sophisticated, for a large ... Continue reading...

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