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

• Autor(a) principal: Mazzu-Nascimento, Thiago
• Data de Publicação: 2022
• Outros Autores: Evangelista, Danilo Nogueira, Abubakar, Obeedu, Sousa, Amanda Soares, Souza, Leandro Cândido de, Chachá, Silvana Gama Florencio, Luporini, Rafael Luis, Domingues, Lucas Vinícius, Silva, Diego Furtado, Nogueira-de-Almeida, Carlos Alberto
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: International Journal of Nutrology (Online)
• Texto Completo: https://ijn.zotarellifilhoscientificworks.com/index.php/ijn/article/view/216
• topic: anemia; jaundice; coronavirus infection; public health; smartphone

Anemia 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.