Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
Article Fingerprint
ReserarchID
B8142
Rapid influenza diagnostic test (RIDT) is one of the most common tools for screening patients suspected of influenza infection. The principle is to detect the surface antigen of influenza virus with known antibodies, and then to interpret it with the naked eye in the form of immune chromatographic as says. It has the advantage of obtaining speedy results (10-30 minutes) and ease of operation (which can be interpreted with the naked eye).There is a variety of rapid influenza diagnostic tests (RIDTs) available in the market, with different sensitivities and specificities depending on the design of the antibody location and reagent composition. Despite its advantages of speed and convenience, a high percentage of test results (20 to 50% or higher) do not correctly reflect the patient’s status. In addition to possible misses in the specimen collection process that will affect the tests; the naked eye may not be able to distinguish the unapparent results and cause false negatives. At the same time, because a healthcare worker may not accurately grasp the time of interpretation, false positives can also occur due to excessive test times. To minimize incorrect diagnoses, we propose an interpretation system using machine vision. The system replaces the function of a healthcare worker by a camera and computer. The camera captures the image of the test piece then sent it to the computer for processing and identification; the result can provide the medical staff reference.
Wen-Tung Hsu. 2020. \u201cA Study of Automated Optical Inspection of Rapid Influenza Diagnostic Tests\u201d. Global Journal of Research in Engineering - A : Mechanical & Mechanics GJRE-A Volume 20 (GJRE Volume 20 Issue A1): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
A Comparative Study of the Effeect of Promotion on Employee
The Problem Managing Bicycling Mobility in Latin American Cities: Ciclovias
Impact of Capillarity-Induced Rising Damp on the Energy Performance of
Rapid influenza diagnostic test (RIDT) is one of the most common tools for screening patients suspected of influenza infection. The principle is to detect the surface antigen of influenza virus with known antibodies, and then to interpret it with the naked eye in the form of immune chromatographic as says. It has the advantage of obtaining speedy results (10-30 minutes) and ease of operation (which can be interpreted with the naked eye).There is a variety of rapid influenza diagnostic tests (RIDTs) available in the market, with different sensitivities and specificities depending on the design of the antibody location and reagent composition. Despite its advantages of speed and convenience, a high percentage of test results (20 to 50% or higher) do not correctly reflect the patient’s status. In addition to possible misses in the specimen collection process that will affect the tests; the naked eye may not be able to distinguish the unapparent results and cause false negatives. At the same time, because a healthcare worker may not accurately grasp the time of interpretation, false positives can also occur due to excessive test times. To minimize incorrect diagnoses, we propose an interpretation system using machine vision. The system replaces the function of a healthcare worker by a camera and computer. The camera captures the image of the test piece then sent it to the computer for processing and identification; the result can provide the medical staff reference.
We are currently updating this article page for a better experience.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
