nilearn for machine learning and statistical analysis of neuroimaging data. Use when working with fMRI, brain connectivity, functional parcellation, GLM contrasts, ICA decomposition, NIfTI image manip
Use with AI
Install the MCP server or CLI to instantly fetch nilearn documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/nilearn
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Bambi (BAyesian Model-Building Interface) is a high-level Python package for fitting Bayesian generalized linear and generalized linear mixed models using a concise, R-style Wilkinson formula syntax.
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QuPath — open-source platform for whole slide image analysis and digital pathology. Provides interactive tools for tissue detection via thresholding, cell detection and positive cell classification (H
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RStan — R interface to Stan for full Bayesian inference via MCMC (NUTS/HMC), approximate inference via ADVI, and penalized MLE via L-BFGS. Compile Stan programs in-process with stan() or stan_model(),
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Stan — probabilistic programming language for Bayesian statistical modeling and high-performance inference. Full Bayesian inference via No-U-Turn Sampler (NUTS/HMC), approximate inference via Automati
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