Question: A deep learning model processes patient data in batches, each batch size a multiple of 11, and the total dataset size is a multiple of 9. If the model must process at least 100 but fewer than 200 patients, what is the smallest possible batch size (in patients) that allows full utilization of both constraints?

Sun, 03 May 2026 05:27:38 +0000

Title: Finding the Smallest Valid Batch Size: A Deep Learning Window with Multiples of 11 and 9 Meta Description:
Optimize deep learning training by determining the smallest batch size that is a multiple of 11 and whose batch capacity multiples a total dataset size that’s a multiple of 9—within a dataset of 100 to 199 patients. Learn how constraints shape model efficiency. --- When deploying deep learning models for patient data processing, choosing an optimal batch size is critical for performance, memory usage, and training speed. In a recent scenario, a healthcare AI system must process patient records in full batches, where each batch size is a multiple of 11, and the total dataset size is a multiple of 9. With the dataset limited to between 100 and 199 patients, researchers seek the smallest valid batch size that satisfies both constraints—ensuring efficient computation and full data utilization.