Published on in Vol 7, No 4 (2019): Oct-Dec
![A Deep Learning Approach for Managing Medical Consumable Materials in Intensive Care Units via Convolutional Neural Networks: Technical Proof-of-Concept Study A Deep Learning Approach for Managing Medical Consumable Materials in Intensive Care Units via Convolutional Neural Networks: Technical Proof-of-Concept Study](https://asset.jmir.pub/assets/4c5307440067ddc38252b4acf789f827.png 480w,https://asset.jmir.pub/assets/4c5307440067ddc38252b4acf789f827.png 960w,https://asset.jmir.pub/assets/4c5307440067ddc38252b4acf789f827.png 1920w,https://asset.jmir.pub/assets/4c5307440067ddc38252b4acf789f827.png 2500w)
Journals
- Nguyen D, Ngo B, vanSonnenberg E. AI in the Intensive Care Unit: Up-to-Date Review. Journal of Intensive Care Medicine 2021;36(10):1115 View
- Martin L, Peine A. Was ist neu … Einsatz von künstlicher Intelligenz in der Intensivmedizin. Der Anaesthesist 2021;70(1):40 View
- Redelmeier D, Thaler R. One nudge for hand hygiene. BMJ Innovations 2021;7(2):249 View
- Luo J, Wang Y, Zhang Y, Yan X, Huang X, Zhao F. Research, development, and evaluation of the practical effect of a storage inflow and outflow management system for consumables in the endocrinology department of a hospital. BMC Medical Informatics and Decision Making 2022;22(1) View
- Arzamasov K, Drogovoz V, Bobrovskaya T, Vladzymyrskyy A. Tele-ultrasound imaging using smartphones and single-board PCs. Digital Diagnostics 2023;4(1):15 View
- See K. Improving environmental sustainability of intensive care units: A mini-review. World Journal of Critical Care Medicine 2023;12(4):217 View
- Meyer L, Stead S, Salge T, Antons D. Artificial intelligence in acute care: A systematic review, conceptual synthesis, and research agenda. Technological Forecasting and Social Change 2024;206:123568 View