For healthcare professionals

Project materials will be posted here as they become available

Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness

Vollmer S, Mateen B A, Bohner G, KirÃ¡ly F J, Ghani R, Jonsson P et al. BMJ 2020;368:l6927

Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

The aim of this article is to provide the reader with a basic understanding of the fundamentals of AI. Its purpose is to demystify this technology for practicing surgeons so they can better understand how and where to apply it.

The ethics of AI in health care: A mapping review

This article maps the ethics of artificial intelligence in healthcare. Its goal is to summarise current debates and identify open questions for future research.

The advent of medical artificial intelligence: lessons from the Japanese approach

Japan has a rich opportunity to lead in the field of medical AI, through the opportunity to curate its 125 million citizen’s data into a central anonymized repository. This article reviews Japan’s approach to AI, including its focus on healthcare and the AI hospitals project.

Health datafication, digital phenotyping and the ‘Internet of Health’

From wearable tech and mobile apps to loyalty cards and online platforms, data gathered from almost every aspect of people’s digital lives increasingly reveals insights about their health. This blog post from the Ada Lovelace foundation considers the impact this 'datafication' of health will have on how we practically and legally define ‘health data’, and on our relationship with our own wellbeing and the healthcare system.

Artificial intelligence and the future of global health

A review on applications of AI in healthcare in low and middle income countries.

Artificial Intelligence: How can youth take part? Declaration on Youth Participation in AI Governance, Youth Department of the Council of Europe,

Organised by the Youth Department of the Council of Europe, between 23and 27 November 2020, this declaration is positioned within the wider framework of the Council of Europe’s youth policy and initiatives that link Artificial Intelligence (AI) and democratic citizenship. The declaration explores issues, challenges and roles that stakeholders can play to secure and enable the participation of young people in AI governance processes at all levels. For AIDE it serves as a useful reminder of the range of Stakeholders that should be included in conversations around AI.

Addenbrooke’s Hospital turns to AI to cut cancer wait times

Addenbrooke’s Hospital has cut radiotherapy preparation tasks by up to 90% using machine learning models built using InnerEye, an artificial intelligence (AI) collaboration between Microsoft Research and the hospital. The drastic cut in administration means clinicians can start potentially life-saving radiotherapy treatments for cancer patients much quicker.

Europe seeks to limit use of AI in society

Away from healthcare, the use of facial recognition for surveillance, or algorithms that manipulate human behaviour, look set to be banned under proposed EU regulations on artificial intelligence. It will be several years before the new rules come into force.

The importance of the assurance that “humans are still in the decision loop” for public trust in artificial intelligence: Evidence from an online experiment

This study investigates the public's initial trust in an artificial intelligence (AI) decision aid utilized in the delivery of public services. Amidst societal anxiety surrounding AI, the study posited that the information communicated to the public about the use of AI matters to the public's initial trust in AI. The level of trust reported by patients in a care plan prepared with AI assistance was greater when they were assured that humans were still in the decision loop.