mims-harvard/SPECTRA
SPECTRA: Spectral framework for evaluation of biomedical AI models
When evaluating AI models in biomedical research, it's crucial to understand how well they generalize to new, unseen data. This tool helps biomedical researchers and AI model developers rigorously test model performance by generating a 'spectrum' of train-test splits with varying degrees of overlap. You input your AI model and a dataset, define how you measure sample similarity, and SPECTRA outputs performance curves showing how your model holds up as data similarity decreases.
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Use this if you need to deeply understand the generalizability of your AI models on biomedical data by analyzing performance across systematically varied data splits.
Not ideal if you are looking for a standard cross-validation or bootstrapping tool, or if your primary interest is not in biomedical AI models.
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Jupyter Notebook
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MIT
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Last pushed
Mar 07, 2025
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