Open-source Python library + no-code web dashboard for evaluating oncology AI mo

<!-- SC_OFF --><div class="md"><p>We’re developing TanML, an MIT-licensed automated model-validation toolkit for tabular machine-learning models.</p> <p>TanML runs locally and

<!-- SC_OFF --><div class="md"><p>Released this week after a few months of work.</p> <p>The problem:</p> <p>Getting Australian medical document training data legally is a dead

<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1v26adz/trinet_v2_opensource_implementation_of_our/"> <img alt="Tri-Net v2: Open-source implementation

<!-- SC_OFF --><div class="md"><p>PyRadiomics is the de facto standard for radiomic feature extraction, but it's CPU-only and takes ~3 seconds per scan. At scale, that's a

<!-- SC_OFF --><div class="md"><p>Built a third-party quality rating system for ML datasets. Multi-oracle (7 scorers across 5 algorithm families), conformal prediction intervals

<!-- SC_OFF --><div class="md"><p>I built a small gradient-boosted tree library based on the screening transform from <a href="https://arxiv.org/abs/2604.01178">&quot;Screening Is

<!-- SC_OFF --><div class="md"><p>Hey everyone,</p> <p>I recently open-sourced a new Python package called <code>ganfs</code> (Generative Adversarial Network Feature Selection),