Dental Research Study: Investigating the oral manifestations of Ehlers Danlos Syndrome.
We are pleased to announce a second round of recruitment has opened for UK adult patients to participate in the #cEDS & #vEDS dental research study by @RestoJimScott
Scholarship of £7500 open to students with a background in social science and/or dentistry taking the Masters in Dental Public Health course at the University of Sheffield in 2023-24 @sarahRbakerDPH@DyerTom435 @sheffunimdh @sheffielduni
Last week, we had the pleasure of hosting @RestoJimScott , a dedicated dentist who is passionate about helping the community understand the importance of dental care and how they can maintain healthy teeth. James shared valuable insights on various aspects of oral hygiene..
Great to have some funding for another round of PPI from @NIHR_RDSYH.
Looking forwards to heading back to @IsraacS to discuss how to understand gum disease 🦠 🦷
The rise of AI is transforming the way we work, live, and interact with each other. If used in the right way, AI could be the perfect co-pilot for dyslexics to really move the world forward. Here’s more: https://t.co/Ow2CbSJYHz
@MadeByDyslexia@Virgin
Thanks to @HanyaMahmood for organising a great evening for our undergraduates @ShefDentistry highlighting the real wins of a academic career. A pleasure to speak! @NIHRcommunity @sheffielduni
The Enhance-D study is a great example of clinical research being done in primary care dental practices to improve patient care involving H and T colleagues. @ShefDentistry@NewcastleDental
What is co-production? Take a look at this handy animation about the key principles that make up co-production and delve deeper into our guidance: https://t.co/KHokZ47FhO
#Coproduction
Really good presentation to start about leadership and management from Professor Andy Parker. Know a bit more about the Atlas experiment for the large Hadron Collider now. Fascinating leadership structures and scale.
Machine learning competitions are often a good indicator of what techniques actually work well in practice on new datasets.
The very comprehensive State of Competitive Machine Learning 2022 report just came out and contained many interesting and surprising insights!
1) As expected, transformers dominate natural language processing (NLP). ALL NLP-related winning solutions used transformers.
2) Convolutional neural networks still dominate computer vision. And EfficientNet is the most popular pretrained architecture for computer vision -- most people finetune pretrained models rather than training from scratch.
3) Almost twice as many winning solutions used k-fold CV instead of a fixed validation set.
4) Kaggle (barely) remains the most popular competition platform.
5) Almost everyone uses Python.
6) Out of 46 winning solutions using deep learning, 44 used PyTorch, and only 2 used TensorFlow.
7) A big surprise for tabular competitions: the reign of XGBoost seems over. While gradient boosting still wins most tabular competitions, LightGBM is now the preferred approach, with CatBoost coming in second. XGBoost is third.
8) Winning solutions of 7 out of the 10 tabular competitions used gradient boosting, 5 out of 10 used deep neural networks (implemented in PyTorch), and most winning solutions were ensemble methods.
Here's a link to the full report: https://t.co/p9dleTZ80R
"Every child is entitled to free treatment by a nonexistent dentist," writes @GeorgeMonbiot
"Some people on benefits also have free & full access to an imaginary service.
"Your rights are guaranteed, up to the point at which you seek to exercise them."👇https://t.co/x5LZdfio0w