Insights

List of Regulations and Standards for Healthcare AI

List of regulations and standards pertaining to healthcare AI, at an international and EU level, as well as nationally in the UK and US.

gliff.ai launches on-premises software for large companies

With the new ‘Enterprise’ product, large companies can opt for an on-premises deployment...

AI Development: It’s Just Science (with bells on it)

The process of high-quality AI development does not need to be esoteric - and neither should it be. It’s just science. With bells on it.

What the Principles for Good Machine Learning Practice mean

gliff.ai's interpretation of the principle to aid implementation by those who are developing machine learning medical devices!

UK to Pilot Algorithmic Impact Assessment (AIA) for Medical AI

Last week, the UK Government announced the pilot of an impact assessment tool to support the ethical development and adoption of artificial intelligence (AI) within healthcare.

A Software Company Embracing Web3

How do we develop AI for real-life healthcare and medical uses? This is where other key aspects of Web3 become central components of the gliff.ai’s software.

What’s end-to-end encryption? Why use it in AI Development?

Using end-to-end encryption within AI development will help you towards meeting standards for privacy and security. And more.

Streamlining Clinical Research and AI Development using Junior Doctors in Medical Image Analysis

By using gliff.ai for medical image analysis, the OCTAHEDRON team has saved time in their AI development in four ways....

A snapshot of gliff.ai’s year in 2021

Durham Company Leads the way in Medical AI

“It is great to be leading the world in software development for AI...”

A Leap Forward in Best Practice for Medical AI Development

Some of the world’s most influential governments in medical regulation have released guidelines for machine learning practices used in the development of medical Artificial Intelligence (AI).

Developing AI to reach the real world

What good are ML models that aim to replicate the world’s greatest medical expertise, if the benefits of such discoveries can not be passed on to patients?

Imaging AI Draws New Battle Grounds for Fighting Counterfeit Products

In Autumn 2021, gliff.ai completed a feasibility study for an anti-counterfeiting imaging artificial intelligence (AI) platform, working in partnership with Durham University and a multinational manufacturer.

Interview with Dr Phil Jackson, Software Engineer

Have you ever wondered what it’s like working at gliff.ai? We asked our Software Engineer, Dr Phil Jackson, about his experience.

Using gliff.ai to Realise the Potential of OCT Data

The aim of the OCT data project is to create a ground-truth annotated dataset that would be utilised for the future development of fully automated AI tool capable of segmenting and quantifying different features in retina images and scans...

gliff.ai Launches Innovative Platform for Developing Trustworthy AI

gliff.ai has launched its innovative software platform, specifically designed to assist the development of trustworthy Artificial Intelligence (AI) by addressing the gap for much-needed Machine Learning Operations (MLOps) products.

Keeping your data secure and private with end-to-end encryption

We at gliff.ai believe that data privacy and security is paramount for the future of FATEful AI.

AI in MedTech — What are we actually doing?

The use of artificial intelligence in medicine and healthcare is thought to be capable of freeing up large quantities of an expert’s time by undertaking exacting and laborious work, saving significant sums of money, improving diagnostic outcomes and democratising medicine by making the world’s experts available globally inside a computer.

The missing people in MLOps

MLOps brings together scientists who develop these early stage AI systems with engineers and operations experts who are able to convert these AI models into reliable and scalable products such as apps on your phone or smart microscopes in the hospital.

‘Coded Bias’ brings bias in AI into mainstream

Coded Bias successfully demonstrates why unregulated, ill-thought-out and opaque approaches to developing AI can easily lead to flawed models that may not only discriminate against certain groups of society but also fail drastically to meet the applications’ original objectives.

Why we’re choosing GNU AGPLv3

gliff.ai believes that we should practice what we preach and want our users to trust that our products, helping them create FATEful AI systems, are FATEful themselves. One obvious way to do this is to make our codes open source and thus enable people to scrutinise our codes and feel confident that they’re doing only what we say they’re doing.

A response to “The Use of Artificial Intelligence in Health Care: Trustworthiness (ANSI/CTA-2090)

This ANSI standard, developed by the US Consumer Technology Association (CTA) Artificial Intelligence (AI) working group, was released in the last week of February 2021. To prove Trustworthiness of an AI in healthcare the standard usefully considers Human, Technical and Regulatory Trust separately but it may end up trying to do too much.

Ethics Statement

gliff.ai was founded on the belief that imaging Artificial Intelligence (AI) can make the world a better place. We are committed to advancing the state-of-the-art whilst practising and encouraging what we call FATEful AI.