Case Study: 365mc achieves safer, more accurate and efficient liposuction with Microsoft Azure IoT and Machine Learning

365mc improves the efficiency and safety of Liposuction with data analysis based on Microsoft Azure IoT and Machine Learning

365mc is a South Korean obesity-care hospital that performs millions of liposuction treatments across 17 branches. Because liposuction traditionally depended on a surgeon’s feel—requiring 12,000–20,000 cannula movements per operation and generating up to ~180,000 datapoints per surgery—365mc wanted to digitize those movements to reduce variability, prevent tissue damage, and improve overall safety and outcomes.

To solve this, 365mc developed the M.A.I.L. system: a sensor-equipped cannula that streams motion data to Microsoft Azure IoT Suite and Microsoft Azure Machine Learning for real-time collection and pattern analysis. By analyzing billions of data points (about 2 billion over two years), the system detects abnormal movements, provides immediate feedback and post-op comparisons, and has measurably increased the accuracy, safety, and training speed for surgeons while enabling plans to scale the technology more widely.

365mc

Nam-Chul Kim

CEO and Dr. Representative