Abstract This study investigates minor disruptions in the Keda Torus eXperiment (KTX) and presents a deep learning-based approach for disruption prediction. Plasma disruptions in magnetic confinement devices are critical to operational safety, making their prediction essential. Machine learning methods provide a foundation for predicting disruptions and informing mitigation strategies. Although the stabilizing shell in reverse-field pinch devices typically suppresses disruptions, minor disruptio