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Found 4 papers, 1 papers with code
Segmentation, Classification and Interpretation of Breast Cancer Medical Images using Human-in-the-Loop Machine Learning
In this case a doctor-in-the-loop approach is proposed to leverage human expertise in dealing with large and complex data.
Evaluating Explanatory Capabilities of Machine Learning Models in Medical Diagnostics: A Human-in-the-Loop Approach
These features are not only used as a dimensionality reduction approach for the machine learning models, but also as way to evaluate the explainability capabilities of the different models using agnostic and non-agnostic explainability techniques.
An effective and efficient green federated learning method for one-layer neural networks
Federated learning (FL) is one of the most active research lines in machine learning, as it allows the training of collaborative models in a distributed way, an interesting option in many real-world environments, such as the Internet of Things, allowing the use of these models in edge computing devices.
A Convolutional Network for Sleep Stages Classification
Sleep stages classification is a crucial task in the context of sleep studies.
