LiverDiseasePrediction

AI Toolkit for Healthcare Imaging

Reading list for research topics in multimodal machine learning

? Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values

ESB, SOA, REST, APIs and Cloud Integrations in Python

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

rPPG-Toolbox: Deep Remote PPG Toolbox (NeurIPS 2023)

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

[NeurIPS 2021] Multiscale Benchmarks for Multimodal Representation Learning

Medical Q&A with Deep Language Models