CLASSify- A Web-based Tool for Machine Learning

Clinicians often produce large amounts of data from various sources, such as patient metrics, drug components, and treatment outcomes. Classifying this data is key to gaining insights or identifying trends that could lead to improvements in patient care. However, this is often a time-consuming process. While clinicians are interested in using AI to address this challenge, they may lack the technical skillsets needed to leverage the technology. CAAI developed CLASSify to make machine learning (ML) easier and more accessible for clinicians and other users who may not have technical or programming backgrounds. CLASSify provides an easy-to-use, web-based platform to train and evaluate ML classification models on any tabular data. Users can simply upload their dataset to the site using the default settings, or selecting their specific training parameters. The job will be sent off to train all chosen models and provide results in the form of tables and visualizations. CLASSify also provides options for synthetic data generation to bolster imbalanced class labels or create entirely new datasets. Additionally, CLASSify determines explainability scores that provide insight into which features of the data are most important to the models’ predictions. As a self-service, all-in-one ML tool, CLASSify allows clinicians to effortlessly compare models, gather results, and download any generated artifacts for later use.

Key features of CLASSify:

• Customizable training parameters
• Results in tables or visualizations
• Synthetic data generation to bolster imbalanced class labels or create new datasets
• Explainability scores for deeper insights
• Easy model comparison for faster decision-making