Abstract: An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.

Abstract: A respiratory status classifying method is for classifying as one of at least two respiratory statuses and includes an original physiological parameter inputting step, an original chest image inputting step, a characteristic physiological parameter generating step, a characteristic chest image generating step, a training step and a classifier generating step. The characteristic chest image generating step includes processing at least a part of the original chest images, segmenting images of a left lung, a right lung and a heart from each of the original chest images that are processed, and enhancing image data of the images being segmented, so as to generate a plurality of characteristic chest images. The training step includes training two respiratory status classifiers using a plurality of characteristic physiological parameters and the characteristic chest images by at least one machine learning algorithm.

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: An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.

Abstract: A respiratory status classifying method is for classifying as one of at least two respiratory statuses and includes a training's physiological parameter inputting step, a training's chest image inputting step, a characteristic physiological parameter generating step, a characteristic chest image generating step, a training step and a classifier generating step. The characteristic chest image generating step includes processing at least a part of the training's chest images, segmenting images of a left lung, a right lung and a heart from each of the training's chest images that are processed, and enhancing image data of the images being segmented, so as to generate a plurality of characteristic chest images. The training step includes training a plurality of characteristic physiological parameters and the characteristic chest images by at least one machine learning algorithm.

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.

Abstract: In a method for monitoring water level of a water body, a monitoring system is configured to: capture a current image that has a portion of the water body, and a remaining portion aside from the portion of the water body; process the current image into a processed image that includes a water body region corresponding to the portion of the water body, and a background region corresponding to the remaining portion of the current image; mark, on the processed image, a plurality of virtual alert points according to a predetermined water level of the water body; determine whether at least one of the virtual alert points is located within the water body region of the processed image; and generate a monitoring result according to the determination thus made.

Abstract: In a method for monitoring water level of a water body, a monitoring system is configured to: capture a current image that has a portion of the water body, and a remaining portion aside from the portion of the water body; process the current image into a processed image that includes a water body region corresponding to the portion of the water body, and a background region corresponding to the remaining portion of the current image; mark, on the processed image, a plurality of virtual alert points according to a predetermined water level of the water body; determine whether at least one of the virtual alert points is located within the water body region of the processed image; and generate a monitoring result according to the determination thus made.

Abstract: A space position device capable of generating position signals according to its position in space is used in the camera control system for tracking an object. The space position device generates and transmits its position signals to a control unit every predetermined time interval. The control unit then generates control command for controlling a camera to rotate upward/downward, leftward/rightward, zoom in or zoom out according to the generated position signals such that the camera adjusts its focus on the space position device for tracking an object automatically.

Abstract: The synchronous briefing or visual playback in different areas and capability of receiving multiple image sources are achieved by connecting various briefing subsystems in different areas via the Internet. One or more image sources are configured in each briefing subsystem and each connected to a server of the subsystem via physical or wireless network. The server of each briefing subsystem transmits briefing or image data to a playback device for outputting purpose via physical or wireless network. The internet-connected servers in all the briefing subsystems are capable of transmitting briefing or image data to one another via the Internet such that briefing or image outputting in one subsystem can be synchronously performed in other subsystems.