Literature DB >> 27100940

Prick test: evolution towards automated reading.

X Justo1, I Díaz1, J J Gil1, G Gastaminza2.   

Abstract

The prick test is one of the most common medical methods for diagnosing allergies, and it has been carried out in a similar and laborious manner over many decades. In an attempt to standardize the reading of the test, many researchers have tried to automate the process of measuring the allergic reactions found by developing systems and algorithms based on multiple technologies. This work reviews the techniques for automatic wheal measurement with the aim of pointing out their advantages and disadvantages and the progress in the field. Furthermore, it provides a classification scheme for the different technologies applied. The works discussed herein provide evidence that significant challenges still exist for the development of an automatic wheal measurement system that not only helps allergists in their medical practice but also allows for the standardization of the reading and data exchange. As such, the aim of the work was to serve as guideline for the development of a proper and feasible system.
© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  allergic reaction; automatic measurement; prick test; wheal

Mesh:

Substances:

Year:  2016        PMID: 27100940     DOI: 10.1111/all.12921

Source DB:  PubMed          Journal:  Allergy        ISSN: 0105-4538            Impact factor:   13.146


  3 in total

1.  Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting.

Authors:  Jesus Pineda; Raul Vargas; Lenny A Romero; Javier Marrugo; Jaime Meneses; Andres G Marrugo
Journal:  PLoS One       Date:  2019-10-21       Impact factor: 3.240

2.  Evaluation of Skin Prick-Test Reactions for Allergic Sensitization in Dogs With Clinical Symptoms Compatible With Atopic Dermatitis. A Pilot Study.

Authors:  Ana M Carmona-Gil; Jorge Sánchez; Juan Maldonado-Estrada
Journal:  Front Vet Sci       Date:  2019-12-17

3.  Thermography based skin allergic reaction recognition by convolutional neural networks.

Authors:  Łukasz Neumann; Robert Nowak; Jacek Stępień; Ewelina Chmielewska; Patryk Pankiewicz; Radosław Solan; Karina Jahnz-Różyk
Journal:  Sci Rep       Date:  2022-02-16       Impact factor: 4.379

  3 in total

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