Objective. Acute hypotension episode (AHE) is one of the most critical complications in intensive care unit (ICU). A timely and precise AHE prediction system can provide clinicians with sufficient time to respond with proper therapeutic measures, playing a crucial role in saving patients' lives. Recent studies have focused on utilizing more complex models to improve predictive performance. However, these models are not suitable for clinical application due to limited computing resources for bedside monitors. Approach. To address this challenge, we propose an efficient lightweight dilated shuffle group network. It effectively incorporates shuffling operations into grouped convolutions on the channel and dilated convolutions on the temporal dimension, enhancing global and local feature extraction while reducing computational load. Main results. Our benchmarking experiments on the MIMIC-III and VitalDB datasets, comprising 6036 samples from 1304 patients and 2958 samples from 1047 patients, respectively, demonstrate that our model outperforms other state-of-the-art lightweight CNNs in terms of balancing parameters and computational complexity. Additionally, we discovered that the utilization of multiple physiological signals significantly improves the performance of AHE prediction. External validation on the MIMIC-IV dataset confirmed our findings, with prediction accuracy for AHE 5 min prior reaching 93.04% and 92.04% on the MIMIC-III and VitalDB datasets, respectively, and 89.47% in external verification. Significance. Our study demonstrates the potential of lightweight CNN architectures in clinical applications, providing a promising solution for real-time AHE prediction under resource constraints in ICU settings, thereby marking a significant step forward in improving patient care.
Medical physics and biophysics

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Roberts Best Paper Prize 2022
Physics in Medicine & Biology (PMB), in association with the journal owners, the Institute of Physics and Engineering in Medicine (IPEM), jointly award this prize in honour of the first editor of PMB, John Roberts, who served from 1956 to 1960. The 2022 best paper is presented to authors, Jungwook Shin, Shu Xing, Lucas McCullum, Abdelkhalek Hammi, Jennifer Pursley, Camilo A Correa, Julia Withrow, Sean Domal, Wesley Bolch, Harald Paganetti and Clemens Grassberger, for their paper HEDOS&mdashXa computational tool to assess radiation dose to circulating blood cells during external beam radiotherapy based on whole-body blood flow simulations.
Welcome to Katia Parodi, new Editor-in-Chief of Physics in Medicine & Biology.
We welcome PMB's new Editor-in-Chief, Professor Katia Parodi of Ludwig Maximilian University, Munich. "It is a great honour to become the new Editor-in-Chief of PMB...we will do our best to continue expanding the scope of the journal with exciting new trends, while preserving well established topical areas, focusing on therapeutic procedures and medical imaging. Our mission is to attract ground-breaking papers and offer the best experience to our authors and readers for a rapid and broad dissemination of cutting-edge physics research for medicine, physiology and biology". Find out more here.