IoT-Enabled Personalized ICU Nutrition Plans: An Intelligent Approach Through Decision Tree Algorithm

Personalized care and continuous patient monitoring are signs of critical care units (ICUs), where the IoT may significantly enhance healthcare delivery. Optimal nutrition plans for ICU patients, taking into account their unique requirements, preferences, and medical issues, is a difficulty in IoT-enabled healthcare. Using Decision Tree (DT) algorithms, it provides a smart method for creating individualized ICU nutrition plans in this research. In the ICU, users take readings of vital signs using internet-connected equipment, including temperature, heart rate, blood oxygen saturation, and body mass index. After that, it sorts the patients into several groups according to their nutritional needs and potential dangers using DT algorithms that are used with the collected data. The system for patients is created using the categorization findings; these plans consider the patient's calorie, protein, fluid, and micronutrient consumption. By comparing the technique to the current ones and utilizing a simulated dataset of ICU patients, it assesses how well it performs. Better health outcomes and lower healthcare costs may be achieved by using the technique to create more precise and efficient diet plans for ICU patients.