Avaliação Automatizada de Qualidade e Adesão ao Protocolo de Aquisição de Imagens em Exames de Teledermatologia
Resumo
Este trabalho aborda o aspecto negligenciado da avaliação da qualidade da imagem e da adesão aos protocolos de aquisição em teledermatologia, propondo aprendizado de máquina para automação. Concentra-se em dois protocolos: Imagem de Aproximação e Imagem Panorâmica, predominantes nos protocolos de exames do STT/SC. A validação envolveu métricas padrão de aprendizado de máquina e um estudo de concordância entre avaliadores com 11 dermatologistas. A abordagem combinada alcançou uma concordância de 96,68% em estudo interavaliadores, demonstrando o potencial desta automatização da avaliação da qualidade da imagem e da adesão ao protocolo em teledermatologia em agilizar a análise especializada.Referências
Chan, S., Reddy, V., Myers, B., Thibodeaux, Q., Brownstone, N., and Liao, W. (2020). Machine learning in dermatology: Current applications, opportunities, and limitations. Dermatology and Therapy, 10(3):365–386. Publisher: Springer Science and Business Media LLC.
High, W., Houston, M., Calobrisi, S., Drage, L., and McEvoy, M. (2000). Assessment of the accuracy of low-cost store-and-forward teledermatology consultation. Journal of the American Academy of Dermatology, 42:776–83.
Inacio, A. d. S., Andrade, R., Wangenheim, A. v., and Macedo, D. D. J. (2014). Designing an information retrieval system for the STT/SC. In 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom). IEEE.
INCA (2023). Estimate | 2023 Cancer Incidence in Brazil. Instituto Nacional de Câncer (Brasil).
Lasierra, N., Alesanco, A., Gilaberte, Y., Magallón-Botaya, R., and García, J. (2012). Lessons learned after a three-year store and forward teledermatology experience using internet: Strengths and limitations. International journal of medical informatics, 81:332–43.
Levin, Y. and Warshaw, E. (2009). Teledermatology: A review of reliability and accuracy of diagnosis and management. Dermatologic clinics, 27:163–76, vii.
Mckoy, K., Antoniotti, N., Armstrong, A., Bashshur, R., Bernard, J., Bernstein, D., Burdick, A., Edison, K., Goldyne, M., Kovarik, C., Krupinski, E., Kvedar, J., Larkey, J., Lee-Keltner, I., Lipoff, J., Oh, D., Pak, H., Seraly, M., Siegel, D., and Whited, J. (2016). Practice guidelines for teledermatology. Telemedicine and e-Health, 22.
Navarrete-Dechent, C., Dusza, S. W., Liopyris, K., Marghoob, A. A., Halpern, A. C., and Marchetti, M. A. (2018). Automated dermatological diagnosis: Hype or reality? Journal of Investigative Dermatology, 138(10):2277–2279.
Nobre, L. F. and von Wangenheim, A. (2012). Development and implementation of a statewide telemedicine/telehealth system in the state of santa catarina, brazil. In Technology Enabled Knowledge Translation for eHealth: Principles and Practice, pages 379–400. Springer New York, New York, NY.
Pai, V. V. and Pai, R. B. (2021). Artificial intelligence in dermatology and healthcare: An overview. Indian Journal of Dermatology, Venereology and Leprology, 0:1–11. Publisher: Scientific Scholar.
Pompl, R., Bunk, W., Dersch, D. R., Horsch, A., Stolz, W., Abmayr, W., Brauer, W., Gläßl, A., Schiffner, R., and Morfill, G. (1999). Charakterisierung der farbeigenschaften melanozytärer hautveränderungen zur unterstützung der früherkennung des malignen melanoms. In Informatik aktuell, pages 160–164. Springer Berlin Heidelberg.
Ribeiro, R. d. P. e. S. and von Wangenheim, A. (2024). Automated image quality and protocol adherence assessment of examinations in teledermatology: First results. Telemedicine and e-Health, 30(4):994–1005. PMID: 37930716.
Thomsen, K., Iversen, L., Titlestad, T. L., and Winther, O. (2019). Systematic review of machine learning for diagnosis and prognosis in dermatology. Journal of Dermatological Treatment, 31(5):496–510.
Wagner, H. M. and Picolotto de Lara, M. (2022). Manual teledermatologia: Técnico.
Wangenheim, A. v. and Nunes, D. H. (2018a). Creating a web infrastructure for the support of clinical protocols and clinical management: An example in teledermatology. Telemedicine and e-Health, 25:781–790.
Wangenheim, A. v. and Nunes, D. H. (2018b). Direct impact on costs of the teledermatology-centered patient triage in the state of santa catarina analysis of the 2014-2018 data. INCoD/UFSC.
High, W., Houston, M., Calobrisi, S., Drage, L., and McEvoy, M. (2000). Assessment of the accuracy of low-cost store-and-forward teledermatology consultation. Journal of the American Academy of Dermatology, 42:776–83.
Inacio, A. d. S., Andrade, R., Wangenheim, A. v., and Macedo, D. D. J. (2014). Designing an information retrieval system for the STT/SC. In 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom). IEEE.
INCA (2023). Estimate | 2023 Cancer Incidence in Brazil. Instituto Nacional de Câncer (Brasil).
Lasierra, N., Alesanco, A., Gilaberte, Y., Magallón-Botaya, R., and García, J. (2012). Lessons learned after a three-year store and forward teledermatology experience using internet: Strengths and limitations. International journal of medical informatics, 81:332–43.
Levin, Y. and Warshaw, E. (2009). Teledermatology: A review of reliability and accuracy of diagnosis and management. Dermatologic clinics, 27:163–76, vii.
Mckoy, K., Antoniotti, N., Armstrong, A., Bashshur, R., Bernard, J., Bernstein, D., Burdick, A., Edison, K., Goldyne, M., Kovarik, C., Krupinski, E., Kvedar, J., Larkey, J., Lee-Keltner, I., Lipoff, J., Oh, D., Pak, H., Seraly, M., Siegel, D., and Whited, J. (2016). Practice guidelines for teledermatology. Telemedicine and e-Health, 22.
Navarrete-Dechent, C., Dusza, S. W., Liopyris, K., Marghoob, A. A., Halpern, A. C., and Marchetti, M. A. (2018). Automated dermatological diagnosis: Hype or reality? Journal of Investigative Dermatology, 138(10):2277–2279.
Nobre, L. F. and von Wangenheim, A. (2012). Development and implementation of a statewide telemedicine/telehealth system in the state of santa catarina, brazil. In Technology Enabled Knowledge Translation for eHealth: Principles and Practice, pages 379–400. Springer New York, New York, NY.
Pai, V. V. and Pai, R. B. (2021). Artificial intelligence in dermatology and healthcare: An overview. Indian Journal of Dermatology, Venereology and Leprology, 0:1–11. Publisher: Scientific Scholar.
Pompl, R., Bunk, W., Dersch, D. R., Horsch, A., Stolz, W., Abmayr, W., Brauer, W., Gläßl, A., Schiffner, R., and Morfill, G. (1999). Charakterisierung der farbeigenschaften melanozytärer hautveränderungen zur unterstützung der früherkennung des malignen melanoms. In Informatik aktuell, pages 160–164. Springer Berlin Heidelberg.
Ribeiro, R. d. P. e. S. and von Wangenheim, A. (2024). Automated image quality and protocol adherence assessment of examinations in teledermatology: First results. Telemedicine and e-Health, 30(4):994–1005. PMID: 37930716.
Thomsen, K., Iversen, L., Titlestad, T. L., and Winther, O. (2019). Systematic review of machine learning for diagnosis and prognosis in dermatology. Journal of Dermatological Treatment, 31(5):496–510.
Wagner, H. M. and Picolotto de Lara, M. (2022). Manual teledermatologia: Técnico.
Wangenheim, A. v. and Nunes, D. H. (2018a). Creating a web infrastructure for the support of clinical protocols and clinical management: An example in teledermatology. Telemedicine and e-Health, 25:781–790.
Wangenheim, A. v. and Nunes, D. H. (2018b). Direct impact on costs of the teledermatology-centered patient triage in the state of santa catarina analysis of the 2014-2018 data. INCoD/UFSC.
Publicado
25/06/2024
Como Citar
RIBEIRO, Rodrigo P. S.; WANGENHEIM, Aldo von.
Avaliação Automatizada de Qualidade e Adesão ao Protocolo de Aquisição de Imagens em Exames de Teledermatologia. In: PRÊMIO ARTUR ZIVIANI - CONCURSO DE TESES E DISSERTAÇÕES (MESTRADO) - SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 24. , 2024, Goiânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 55-60.
ISSN 2763-8987.
DOI: https://doi.org/10.5753/sbcas_estendido.2024.2256.
