9 results about "Individual analysis" patented technology

Disclosed herein are methods, non-transitory computer readable media, systems, and kits for performing an intra-individual analysis for determining presence or absence of a health condition in an individual. Specifically, the intra-individual analysis involves combining sequence information from target nucleic acids with sequence information from reference nucleic acids obtained from the individual. The target nucleic acids include signatures that may be informative for determining presence or absence of the health condition and the reference nucleic acids include baseline biological signatures of the individual. By combining sequence information from the target nucleic acids and the reference nucleic acids, the resulting generated signal is more informative for determining presence or absence of the health condition in comparison to sequence information of the target nucleic acids alone.

The present invention provides a dual-processing-based individual analysis device and method using artificial intelligence, and a smart farm monitoring system using the same. [Solution] The method in the smart farm monitoring system 10 includes the steps of collecting target data including video data and sensing data linked to the individual being monitored using an edge device 200, performing an initial analysis using the edge device to input the target data into a first model based on pre-trained artificial intelligence and outputting first analysis data linked to the individual's behavioral patterns, and transmitting the first analysis data and the target data to a main server when the first analysis data meets pre-set detailed analysis conditions.

Disclosed herein are methods, non-transitory computer readable media, systems, and kits for performing a multiple tiered analysis for identifying individuals with a health condition for monitoring, treating, and / or enrolling the individuals in a clinical trial. Specifically, the multiple tiered analysis involves a first screen, which eliminates a large proportion of individuals who are identified as not at risk for a health condition, and a subsequent second analysis which detects presence of a health condition in the remaining individuals. The second analysis includes an intra-individual analysis, which involves combining sequence information from target nucleic acids and reference nucleic acids obtained from the individual. The target nucleic acids include signatures that may be informative for determining presence or absence of the health condition and the reference nucleic acids include baseline biological signatures of the individual. Altogether, the multiple tiered analysis achieves improved performance and accurate identification of individuals with the health condition.

The present application relates to a kind of pronghorn identification system, method, processing device and storage medium based on video tracking, the system includes: data input interface, for receiving the video or image data stream from one or more camera equipment;Data type judging module is used to judge the data type of video or image data stream based on the meta information of video or image data stream;Refinement individual analysis channel is used to accurately track the individual of pronghorn in video or image data stream, trajectory optimization and behavior analysis are carried out to near view data, and the refinement individual analysis result of pronghorn is obtained;Macroscopic group analysis channel is used to carry out population statistics and rhythm analysis to long-range or aerial data in video or image data stream, and the macroscopic group analysis result of pronghorn is obtained;Data output interface is used to output the refinement individual analysis result and macroscopic group analysis result of pronghorn, the present application can be widely applied in computer vision and intelligent monitoring technical field.

This invention provides an individual analysis device and method using an artificial intelligence-based dual-processing platform, as well as a smart farm monitoring system using the same. [Solution] The method in the smart farm monitoring system 10 includes the steps of: collecting target data, including video data and sensing data linked to the individual being monitored, using an edge device 200; performing an initial analysis using the edge device, inputting the target data into a first model of a pre-trained artificial intelligence platform to output first analysis data linked to the individual's behavioral patterns; and transmitting the first analysis data and target data to the main server when the first analysis data satisfies pre-set detailed analysis conditions.

We provide the system. [Solution] In an information processing device, means for activating multiple knowledge processing devices specialized in each specialized field, The aforementioned knowledge processing device has means for accumulating the results of individual analyses, A means by which knowledge processing devices consult with each other based on the aforementioned analysis results and make a final decision, A means of collecting user input data from a terminal and sending it to a database in an organized format, A means of displaying the received analysis results on the user's information terminal, A system that includes this.

Disclosed herein are methods, non-transitory computer readable media, systems, and kits for performing a multiple tiered analysis for identifying individuals with a health condition for monitoring, treating, and / or enrolling the individuals in a clinical trial. Specifically, the multiple tiered analysis involves a first screen, which eliminates a large proportion of individuals who are identified as not at risk for a health condition, and a subsequent second analysis which detects presence of a health condition in the remaining individuals. The second analysis includes an intra-individual analysis, which involves combining sequence information from target nucleic acids and reference nucleic acids obtained from the individual. The target nucleic acids include signatures that may be informative for determining presence or absence of the health condition and the reference nucleic acids include baseline biological signatures of the individual. Altogether, the multiple tiered analysis achieves improved performance and accurate identification of individuals with the health condition.

Disclosed herein are methods, non-transitory computer readable media, systems, and kits for performing a multiple tiered analysis for identifying individuals with a health condition for monitoring, treating, and / or enrolling the individuals in a clinical trial. Specifically, the multiple tiered analysis involves a first screen, which eliminates a large proportion of individuals who are identified as not at risk for a health condition, and a subsequent second analysis which detects presence of a health condition in the remaining individuals. The second analysis includes an intra-individual analysis, which involves combining sequence information from target nucleic acids and reference nucleic acids obtained from the individual. The target nucleic acids include signatures that may be informative for determining presence or absence of the health condition and the reference nucleic acids include baseline biological signatures of the individual. Altogether, the multiple tiered analysis achieves improved performance and accurate identification of individuals with the health condition.

The invention discloses a special child dangerous behavior early warning system based on artificial intelligence. The system comprises a data acquisition module, a data optimization module, a dangerous behavior early warning model establishment module, an early warning model parameter optimization module and a dangerous behavior intelligent early warning module. The invention relates to the technical field of behavior data processing, in particular to a special child dangerous behavior early warning system based on artificial intelligence, which innovatively combines child behavior recognition with behavior scene understanding, introduces an individualized analysis mechanism, and effectively improves the comprehensiveness, accuracy and robustness of dangerous behavior recognition. A child behavior time sequence attention recognition network combining a multi-level residual dense block, a double-branch attention mechanism and a feature step-by-step guide fusion strategy is designed, the accuracy and stability of action recognition are improved, and the accuracy of dangerous behavior recognition is improved; and an improved swarm intelligent optimization algorithm of a multi-branch exploration updating strategy is introduced, so that the recognition accuracy of the dangerous behavior early warning model is improved.