An enhanced grey wolf optimizer boosted machine learning prediction model for patient-flow prediction.

Large and medium-sized general hospitals have adopted artificial intelligence big data systems to optimize the management of medical resources to improve the quality of hospital outpatient services and decrease patient wait times in recent years as a result of the development of medical information technology and the rise of big medical data. However, owing to the impact of several elements, including the physical environment, patient, and physician behaviours, the real optimum treatment effect does not meet expectations. In order to promote orderly patient access, this work provides a patient-flow prediction model that takes into account shifting dynamics and objective rules of patient-flow to handle this issue and forecast patients' medical requirements.

16 × 16 non-blocking silicon optical switch based on electro-optic Mach-Zehnder interferometers.

We experimentally demonstrate a 16 × 16 non-blocking optical switch fabric with a footprint of 10.7 × 4.4 mm.

Seven-bit reconfigurable optical true time delay line based on silicon integration.

We design, fabricate, and characterize a 7-bit reconfigurable optical true time delay line consisting of Mach-Zehnder interferometer (MZI) switches on the silicon photonics platform. Variable optical attenuators (VOAs) are embedded to suppress the inter-symbol crosstalk caused by the finite extinction ratio of switches. The device can provide a maximum of 1.