Smartphone-based photo analysis for the evaluation of anemia, jaundice and COVID-19

Author:

Mazzu-Nascimento Thiago12ORCID,Evangelista Danilo Nogueira1ORCID,Abubakar Obeedu1,Sousa Amanda Soares1ORCID,Souza Leandro Cândido de1ORCID,Chachá Silvana Gama Florencio1ORCID,Luporini Rafael Luis134ORCID,Domingues Lucas Vinícius2,Silva Diego Furtado2ORCID,Nogueira-de-Almeida Carlos Alberto1ORCID

Affiliation:

1. Department of Medicine, Universidade Federal de São Carlos, São Carlos, SP, Brazil

2. Department of Computing, Universidade Federal de São Carlos, São Carlos, SP, Brazil.

3. Department of General Surgery, Santa Casa de São Carlos, São Carlos SP, Brazil

4. Department of Education, Santa Casa de São Carlos, São Carlos SP, Brazil

Abstract

AbstractAnemia and jaundice are common health conditions that affect millions of children, adults, and the elderly worldwide. Recently, the pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), the virus that leads to COVID-19, has generated an extreme worldwide concern and a huge impact on public health, education, and economy, reaching all spheres of society. The development of techniques for non-invasive diagnosis and the use of mobile health (mHealth) is reaching more and more space. The analysis of a simple photograph by smartphone can allow an assessment of a person's health status. Image analysis techniques have advanced a lot in a short time. Analyses that were previously done manually, can now be done automatically by methods involving artificial intelligence. The use of smartphones, combined with machine learning techniques for image analysis (preprocessing, extraction of characteristics, classification, or regression), capable of providing predictions with high sensitivity and specificity, seems to be a trend. We presented in this review some highlights of the evaluation of anemia, jaundice, and COVID-19 by photo analysis, emphasizing the importance of using the smartphone, machine learning algorithms, and applications that are emerging rapidly. Soon, this will certainly be a reality. Also, these innovative methods will encourage the incorporation of mHealth technologies in telemedicine and the expansion of people's access to health services and early diagnosis.

Publisher

Zotarelli-Filho Scientific Works

Reference20 articles.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The application of artificial intelligence in the diagnosis and management of anemia;Iranian Journal of Blood and Cancer;2023-08-01

2. Detection of iron deficiency anemia by medical images: a comparative study of machine learning algorithms;BioData Mining;2023-01-24

3. Early Prediction of Neonatal Jaundice using Artificial Intelligence Techniques;2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM);2022-02-23

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