Natasha Liou
@nsyl3
Obstetrician and gynaecologist in East London
ID: 28554240
03-04-2009 12:44:35
45 Tweet
25 Followers
81 Following
Another absolutely shocking finding from our new research with The Lancet. If you are struggling please remember that there are always people to talk to who are there to listen - you can call Samaritans night or day, 116 123 or email [email protected] #ChangeTheMiscarriageStory
Brilliant presentation by Natasha Liou as a poster pitch finalist at #BBRS22. Such a clear explanation of science that has the potential to really make a difference for patients with UTI. Raj Khasriya Anna David Blair Bell Research Society UCL EGA Institute for Women's Health
UTIs are an under-recognised cause of adverse pregnancy outcomes and morbidity. Diagnosis is complex. Here Natasha Liou outlines an automated diagnostic system. ๐คฏ brilliant. Supervised by the amazing Raj Khasriya Anna David H Horsely Jane Currie UCL EGA Institute for Women's Health Blair Bell Research Society RoyalCollegeObsGyn
We would like to share our thoughts on this paper. The discussion around dysbiosis due to antimicrobials is of course very important and we welcome research in this area. Leah stewart bundrick Chris Harding Ased Ali Prof Jennifer L. Rohn Sheela Swamy CUTIC ๐ฅ๐๐ถ๐๐๐ ๐๐ธ๐๐พ๐๐๐ถ๐ ๐ป
Hi all! Welcome to the BIIG Twitter page - home for everything UTI. Current members are Harry Horsley, Rajvinder Khasriya, Catherine Chieng, Peter Kong and Natasha Liou. Check back often for updates! Raj Khasriya Natasha Liou @ccyun_c
Hi, I'm Natasha! I'm an #ObGyn Dr and PhD student at #BIIG UCL Renal and UCL EGA Institute for Women's Health since '21. I'm interested in the relationship between reproductive hormones and #chronicUTI and improving UTI diagnosis with #MachineLearning. Here's my prev work on UTI: bit.ly/3UxhUuf
We had flash talks by BIIG members and collaborators sharing exciting research! Dr Catherine Chieng, immunology fiend! @ccyun_c Dr Natasha Liou, machine learning enthusiast Natasha Liou Trina De of CASUS, mathematical whiz! Baylie Hochstedler of Loyola, host-microbe expert
Dr Artur Yakimovich Artur Yakimovich of CASUS in Germany came to share about how machine learning can be used in biomedical images to study infection and disease. The potential for image-based ML in this area seems limitless!
It was a truly fabulous afternoon filled with riveting advances in UTI research and rousing stories of Prof that had us both crying and in stitches. We at Bladder Infection and Immunity Group are so proud to be carrying on the legacy of this courageous and brilliant man. Thank you, and see you next year!
We are excited to share our first #BIIG publication! A sincere thanks to the editors Mucosal Immunology for inviting us to write a review on #chronicUTI, and the reviewers for their valuable inputs. Available as pre-proof now: sciencedirect.com/science/articlโฆ
A call to gynaecologists to take head of urinary health through the awesome work of Natasha Liou from UCLH and UCL presented Blair Bell Research Society RoyalCollegeObsGyn who presented the impact of systemic hormones on the bladder immune environment
Amazing, interesting, clear talk by Natasha Liou Natasha Liou at the RoyalCollegeObsGyn Blair Bell Research Society Annual Academic Meeting on the altered bladder immune response in healthy postmenopausal women ๐๐ฉโ๐๐
It's always such a pleasure to attend the RoyalCollegeObsGyn Blair Bell Research Society meeting where some of the best scientific work in O&G in the UK is shared, and even more grateful for the opportunity to present the work of Bladder Infection and Immunity Group ! Bladder, meet my friends Oestrogen and Progesterone.
Our work "A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection" in collaboration with Bladder Infection and Immunity Group has just been published in Scientific Data big kudos to Trina De and Adrian Urbanski Center for Advanced Systems Understanding at HZDR nature.com/articles/s4159โฆ
This paper Scientific Data shows a practical use of #MachineLearning in medicine. It's a promising step towards #BIIG's vision: to deploy microscopy for widespread use in all healthcare locations to diagnose #UTI quickly & accurately so the patients can receive timely treatment.
AI in medicine can only be truly powerful if the training data is clinically relevant. That's why we're proud to share our image dataset of urine from patients suffering from UTIs. Here's to a brighter future for UTI diagnostics! Bladder Infection and Immunity Group Artur Yakimovich nature.com/articles/s4159โฆ