Xiao Liu
@xiaoliu.bsky.social
3.2K followers
220 following
34 posts
Health at Microsoft AI
Deputy Editor @ai.nejm.org
Hon Associate Professor @unibirmingham.bsky.social
Prev Apple, Prev ophthalmology doctor in the NHS
Posts
Media
Videos
Starter Packs
Reposted by Xiao Liu
Reposted by Xiao Liu
Reposted by Xiao Liu
Reposted by Xiao Liu
Reposted by Xiao Liu
Elisabeth Mahase
@emahase.bsky.social
· Apr 7
AI in healthcare: what does good evidence and regulation look like?
Artificial intelligence is infiltrating medicine at many levels, from providing patients with medical advice and summarising patients’ notes to aiding diagnoses. Elisabeth Mahase looks at how the rese...
www.bmj.com
Xiao Liu
@xiaoliu.bsky.social
· Mar 28
Joe Alderman
@jaldmn.bsky.social
· Mar 18
Tackling algorithmic bias by promoting transparency in health datasets (The STANDING Together recommendations)
Health data is highly complex and can be challenging to interpret without knowing the context in which it was created. Data biases can be encoded into
aiforgood.itu.int
Xiao Liu
@xiaoliu.bsky.social
· Jan 31
Reposted by Xiao Liu
Reposted by Xiao Liu
Joe Alderman
@jaldmn.bsky.social
· Dec 18
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
Without careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. One major source of bias is the data that underpins such technologies. The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups. Draft recommendation items were informed by a systematic review and stakeholder survey.
www.thelancet.com
Xiao Liu
@xiaoliu.bsky.social
· Dec 19
Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations
Without careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. O...
tinyurl.com
Xiao Liu
@xiaoliu.bsky.social
· Dec 19
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
Without careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. One major source of bias is the data that underpins such technologies. The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups. Draft recommendation items were informed by a systematic review and stakeholder survey.
www.thelancet.com
Xiao Liu
@xiaoliu.bsky.social
· Dec 4
MHRA trials five innovative AI technologies as part of pilot scheme to change regulatory approach
The pilot scheme, AI Airlock, is designed to help test and improve the rules for AI-powered medical devices to ensure they reach patients quickly, safely and effectively.
www.gov.uk
Reposted by Xiao Liu
Joe Alderman
@jaldmn.bsky.social
· Nov 27
Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review
There are many radiological datasets for breast cancer, some which have supported
the development of AI medical devices for breast cancer screening and image classification.
This review aims to identi...
www.clinicalimaging.org
Reposted by Xiao Liu
Joe Alderman
@jaldmn.bsky.social
· Nov 27
Xiao Liu
@xiaoliu.bsky.social
· Nov 23
Artificial Intelligence Implementation (Healthcare) MSc / PGDip - University of Birmingham
There is an urgent need for leaders of AI implementation across the healthcare workforce of the UK and worldwide. The MSc AI Implementation (Healthcare) programme is designed to address this need.
www.birmingham.ac.uk