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• Build Apps with Streamlit, FastAPI and Docker

Create your own applications with Streamlit, FastAPI and Docker​

During my projects, I like to build concrete applications from the research I conduct. I use them to demonstrate the capacity of a trained model or a pipeline I developed but also use the code in a more general purpose. To build these apps I use a combination of three tools: Streamlit, FastAPI, and Docker. In this post, I first show two examples of applications I’ve created, and then I present the tools with some simple examples of code.

Sunday, April 20, 2025 | 7 minutes Read

[Citation needed] Data usage and citation practices in medical imaging conferences​

Click on the image below to see my oral session at MIDL 2024: Nowadays, the evaluation of models heavily relies on publicly available datasets used as benchmarking. While this could be a nice thing for a fair comparison of different models, we also question the effect of the diversity or more precisely a potential lack of diversity in research papers when selecting the datasets. A gap has been observed between the results showcased by AI models in research and their adoption in clinical workflow, we hypothesise that this gap could partly be a result of an overfitting of research on these datasets and we wanted to evaluate their usage to know if some are more popular than others. While this could seem like a straightforward task we’ll see that because of some elements it turned out to be not so simple.

Tuesday, July 9, 2024 | 9 minutes Read