Deep learning-based method and device for predicting analysis results
AssigneesKwangwoon University Industry-Academic Collaboration Foundation, Catholic Kwandong University Industry Foundation
InventorsJeong Hoon LEE, Ki Baek LEE, Yong Kyoung YOO, Seung Min LEE, Hak Jun LEE, Ji Won MOON
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Abstract
According to a preferred embodiment of the present invention, a deep learning-based method and device for predicting analysis results predict analysis results of immune response assay-based kits, such as that of lateral flow assay (LEA), antigen-antibody-based diagnostic kits and the like on the basis of deep learning, and thus can reduce the time for confirming results.
Claims16
A deep learning-based analysis result predicting method, comprising:
- a step of obtaining a reaction image for a predetermined initial period for an interaction of a sample obtained from a specimen and an optical-based kit;
- and
- a step of predicting a concentration for a predetermined result time on the basis of the reaction image for the predetermined initial period, using a pre-trained and established analysis result prediction model.
A deep learning-based analysis result predicting device which predicts an analysis result based on deep learning, comprising:
- a memory which stores one or more programs to predict an analysis result;
- and
- one or more processors which perform an operation for predicting the analysis result according to one or more programs stored in the memory,
- wherein the processor predicts a concentration for a predetermined result time on the basis of a reaction image of a predetermined initial period for an interaction of a sample obtained from a specimen and an optical-based kit, using a pre-trained and established analysis result prediction model.
A prediction diagnostic device for an on-site diagnostic test, comprising:
- a memory in which instructions required for on-site diagnosis are stored;
- and
- a processor which performs operations for prediction diagnosis according to the execution of the instructions and the operations includes:
- a step of applying a sample obtained from a specimen to a diagnostic kit and obtaining an initial reaction image of a predetermined initial period according to the interaction of the sample and the diagnostic kit;
- and
- a step of predicting a result reaction of a result period after the initial period by applying the reaction image to a pre-trained and established analysis result prediction model.
Dependencies are inferred from the claim text.