youtu.be/_aMJ21HwlT0

torch.autograd.set_detect_anomaly(True) 👍

Yes..No..

To those who like spinach, flex those popeye muscles! 💪

Time will tell..

Ethan's version of me :D

Every pain gives you a lesson and every lesson changes a person

PI and multiple authors writing different sections of the same paper. #AcademicTwitter OpenAcademics PhD Voice - Independently Run PhD_Genie

Level 4 lock down across the country. Back to last year...

Peek a boo

There's always a first time for everything.

What noise annoys an oyster? An annoying noise annoys an oyster. #tonguetwister

<=> IFF If and only if #math #life

Thrilled to share our preprint on use of #SyntheticData in medical imaging research! 📝 arxiv.org/abs/2311.09402 💬 Here is a custom GPT that will answer all your questions about the paper: chat.openai.com/g/g-iCGh2R2QA-… Some key takeaways in a 🧵 /1

Just received my Science Teaching badge from Emory Continuing Education. credly.com/badges/1159dab…

Don't miss the March Radiology: Artificial Intelligence #RadAIchat on Mar. 6 at 8 PM ET on "Defining the ground truth for #AI" moderated by @khosravi_bardia and panelists Laura Heacock, MD Shahriar Faghani MD Kirti Magudia, MD PhD Theo Dapamede #radiomics #AI #ML #DL #radres RSNA Charles Kahn, MD Hesham Elhalawani

Ground truth labels can be used as benchmark for the performance of the model. This paper by Imon Banerjee shows examples of self-supervised learning tasks evaluated on different ground truths based on their specific downstream task #RadAIchat medrxiv.org/content/10.110…

Training set is used to train the model's weights and biases. Validation is used to perform hyperparameter tuning or to select the best model and the test sets are used to evaluate the model's performance. The test sets may be from internal or external datasets. #RadAIchat

Similar to the reporting using the TRIPOD statement, journals could ensure authors follow a similar standard reporting framework, for example: bmjopen.bmj.com/content/11/7/e… #RadAIchat

🚀 @TheoDapamede and I are thrilled to announce #RadPrompter - a Python package for simplified, reproducible, and composable #LLM prompting, providing a flexible framework for crafting complex prompts from reusable components. 1/7