Responsible ML
Having Fun while building Responsible ML models
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Deep look into classical image processing methods for segmentation
Deep look into classical image processing methods for segmentation
In publications and tools for image data, we hear more and more about the usefulness of deep neural network models. Day by day, research…
survex: model-agnostic explainability for survival analysis
survex: model-agnostic explainability for survival analysis
In this blog, we’d like to cover how model explainability can help make informed choices when working with survival models by showcasing…
Large-scale anonymization of medical imaging data in the DICOM format
Large-scale anonymization of medical imaging data in the DICOM format
Managing experiment metadata “like a MLOps” — Neptune
Managing experiment metadata “like a MLOps” — Neptune
One day comes the great news: the data is available for training. Now, it is the time to start training. We have the goals we want to meet…
LIMEcraft: handcrafted superpixel selection and inspection for Visual eXplanations
LIMEcraft: handcrafted superpixel selection and inspection for Visual eXplanations
The lack of possibility to interact with explanations makes it difficult to verify and understand exactly how the ML model works. The…
How many languages do we need to learn about responsible machine learning? useR! 2022 Conference
How many languages do we need to learn about responsible machine learning? useR! 2022 Conference
It might seem that, we don’t have much choice, because the most popular languages in data science are R and Python or if you prefer Python…
RadioTator: A Tailored Tool for Rapid Medical Text Annotation
RadioTator: A Tailored Tool for Rapid Medical Text Annotation
Creating an annotation app for text data to use for radiologists.
Radiologists’ nightmare — segmentation masks
Radiologists’ nightmare — segmentation masks
This blog is the second in our xLungs series about the Responsible Artificial Intelligence for Lung Diseases project. You can check out…
Towards the largest database of Polish lung medical images
Towards the largest database of Polish lung medical images
AI in healthcare is gaining more at more attention. In MI2DataLab, we work on this area in the project: “xLungs — Responsible Artificial…
Responsible Machine Learning for Survival Analysis
Responsible Machine Learning for Survival Analysis
A brief introduction to survival analysis and the use of machine learning models in this area
Year 2021 under the MIcroscope
Year 2021 under the MIcroscope
The end of the year is a good time to summarize. So, what has happened in 2021 in the MI2 group?
What should you know before publishing your first AI research paper?
What should you know before publishing your first AI research paper?
There are a few tools without which I couldn’t work and write research papers.
Posters that change the perspective on climate and the environment
Posters that change the perspective on climate and the environment
How to cover important topics in an interesting and readable way?
Two day trainings ‘Introduction to Responsible ML in R or Python’— schedule for 2022
Two day trainings ‘Introduction to Responsible ML in R or Python’— schedule for 2022
Based on our experience in the area of Responsible Machine Learning, developed a unique two-day hands-on training. Jump into the topic of…
Backstage: The Hitchhiker’s Guide to Responsible Machine Learning
Backstage: The Hitchhiker’s Guide to Responsible Machine Learning
A month ago we released an educational comic in the area of Interpretable Machine Learning/Explanatory Model Analysis titled ,,The…
Explaining correlated variables — how dalex makes it possible?
Explaining correlated variables — how dalex makes it possible?
The short answer is the Aspect module, which you can read about here. But how does this module work?
Sickest-first policy & predictive models for liver transplant candidates in the US
Sickest-first policy & predictive models for liver transplant candidates in the US
Liver (or in Old English lifer) is referring to the heaviest internal organ in the human body that quietly runs for 24 hours a day.
Interpretable Segmentation of Medical Free-Text Records Based on Word Embeddings
Interpretable Segmentation of Medical Free-Text Records Based on Word Embeddings
A summary of lastly published paper.
Manipulating explainability and fairness in machine learning
Manipulating explainability and fairness in machine learning
toward trustworthy AI..
Guide through jungle of models! What’s more about the forester R package?
Guide through jungle of models! What’s more about the forester R package?
Welcome to the second part of the forester blog. In the previous part, we explained the main idea of the forester package, the motivations…
FairPAN — bringing fairness to neural networks
FairPAN — bringing fairness to neural networks
Achieving fairness throughout adaptation of GANs
Transfer learning for tabular data
Transfer learning for tabular data
The summary of the metaMIMIC article regarding hyperparameter transferability between medical domain prediction tasks
forester: An AutoML R package for Tree-based Models
forester: An AutoML R package for Tree-based Models
Have you ever spent the whole day applying different Machine Learning (ML) algorithms from several libraries, coping with a legion of…