Abstract: A bloodstream infection predicting system and a method thereof are proposed. The memory unit stores a plurality of historical medical data, the real-time data to be tested and a machine learning algorithm. The processor is configured to implement a bloodstream infection predicting method. The bloodstream infection predicting method includes reading the historical medical data from the memory unit, training the historical medical data to generate a bloodstream infection prediction model, reading the real-time data to be tested of the patient from the memory unit, and inputting the real-time data to be tested into the bloodstream infection prediction model to generate the bloodstream infection risk probability. The real-time data to be tested includes an intensive care unit detecting data and a blood inspection data of the patient. The intensive care unit detecting data and the blood inspection data are detected during a feature window time interval.

Abstract: A medical care system for assisting multi-diseases decision-making and real-time information feedback with artificial intelligence technology provided by the invention is capable of obtaining N training models respectively by mathematically operating M different diseases correspondingly based on a batch of collected medical information, obtaining inference results related to at least two diseases by inputting a single patient's data into all or part of the training models to perform mathematical calculation, at the same time, receiving feedback from professionals on the inference results to effectively integrate objective medical data of the patient with subjective medical data of the professionals, and constructing a multi-diseases data model based on the integrated data to be used as a tool for assisting multi-diseases decision-making.