Machine Learning
DataNinja
Introduction DataNinja is a full-stack machine learning workbench designed for object detection tasks. It provides a browser-based interface to manage datasets, configure and train detection models, evaluate results, and, most distinctively, push trained models to embedded hardware in a single workflow. The motivation behind the project was to bridge the gap between the server side (where GPUs live and models are trained) and the edge side (where inference actually runs, often on low-power embedded SoCs or FPGAs). Most open-source ML tools at the time handled one or the other; DataNinja treats them as a single, connected pipeline.
Similar Patient Finder
GitLab Open Source Introduction Similar Patient Finder (SPF) is a web-based clinical decision support tool that helps physicians explore patient similarities at the molecular level. Given a dataset of high-throughput gene expression profiles, optionally paired with clinical metadata, SPF runs a configurable analysis pipeline and renders the results as an interactive 2D patient map, making it easier to identify disease subtypes, staging, and appropriate therapy options. The motivation was that raw genomic data is too high-dimensional for direct inspection. SPF bridges the gap between bioinformatics methods and clinical workflows by wrapping a full preprocessing-to-visualization pipeline in a browser-based interface that requires no command-line work from the physician.