LOOCV is particularly useful in scenarios where the dataset is small, which is a common situation in rare cancer studies or initial phases of research. It is also beneficial when the primary goal is to obtain an unbiased performance estimate of a model. For example, when validating a new diagnostic tool or biomarker that promises a breakthrough in early detection of specific cancers, LOOCV can provide insights into the tool's generalizability.
