A statistical machine learning toolbox for estimating models, distributions, and functions with context-specific parameters with applications to biological and medical systems.

Built using Contextualized.ML

BioContextualized contains:

pip install git+https://github.com/blengerich/BioContextualized.git

• Automated Interpretable Discovery of Heterogeneous Treatment Effectiveness: A COVID-19 Case Study
• NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters
• Discriminative Subtyping of Lung Cancers from Histopathology Images via Contextual Deep Learning
• Personalized Survival Prediction with Contextual Explanation Networks

• Sample-Specific Models for Interpretable Analysis with Applications to Disease Subtyping

Please get in touch with any questions, feature requests, or applications.