Exploring Big Data: A Clinicians Guide to Unsupervised Machine Learning .

Over 2.5 quintillion bytes of data are generated daily on the internet, and with this surge has come a new wave of machine learning tools designed to analyze it. These tools are now entering clinical settings with the promise of transforming medical practice. It’s essential that clinicians begin to understand these technologies—how they work, what they can do, and where their limitations lie. Building on a prior exploration of supervised learning, this piece highlights the principles and practical uses of unsupervised machine learning. From clustering and dimensionality reduction to self-supervised learning, it introduces tools that help uncover structure in data without relying on predefined labels.