This paper is in the following e-collection/theme issue:

Formative Studies and eHealth/mHealth Development (524) Malaria Surveillance and Prevention (26) Design and Formative Evaluation of Mobile Apps (694) mHealth in a Clinical Setting (615) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (565)

Published on in Vol 6, No 4 (2017): April

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis

Authors of this article:

Allisson Dantas Oliveira1, 2 Author Orcid Image ;   Clara Prats3 Author Orcid Image ;   Mateu Espasa4 Author Orcid Image ;   Francesc Zarzuela Serrat4 Author Orcid Image ;   Cristina Montañola Sales3 Author Orcid Image ;   Aroa Silgado4 Author Orcid Image ;   Daniel Lopez Codina3 Author Orcid Image ;   Mercia Eliane Arruda5, 6 Author Orcid Image ;   Jordi Gomez i Prat4 Author Orcid Image ;   Jones Albuquerque1, 6 Author Orcid Image
Article Authors Cited by (35) Tweetations (25) Metrics

Journals

  1. de Araújo A, de Araujo M, Cavalcanti T, de Lacerda Vidal C, da Silva M. DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya. Medical & Biological Engineering & Computing 2020;58(11):2657 View
  2. Guo J, Li B. The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries. Health Equity 2018;2(1):174 View
  3. Jacob S, Prasad K, Rao P, Kamath A, Hegde R, Baby P, Rao R. Computerized Morphometric Analysis of Eryptosis. Frontiers in Physiology 2019;10 View
  4. Leal Neto O, Cruz O, Albuquerque J, Nacarato de Sousa M, Smolinski M, Pessoa Cesse E, Libel M, Vieira de Souza W. Participatory Surveillance Based on Crowdsourcing During the Rio 2016 Olympic Games Using the Guardians of Health Platform: Descriptive Study. JMIR Public Health and Surveillance 2020;6(2):e16119 View
  5. Loddo A, Di Ruberto C, Kocher M. Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology. Sensors 2018;18(2):513 View
  6. Alami H, Rivard L, Lehoux P, Hoffman S, Cadeddu S, Savoldelli M, Samri M, Ag Ahmed M, Fleet R, Fortin J. Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries. Globalization and Health 2020;16(1) View
  7. Hosny A, Aerts H. Artificial intelligence for global health. Science 2019;366(6468):955 View
  8. Yu H, Yang F, Rajaraman S, Ersoy I, Moallem G, Poostchi M, Palaniappan K, Antani S, Maude R, Jaeger S. Malaria Screener: a smartphone application for automated malaria screening. BMC Infectious Diseases 2020;20(1) View
  9. Asadzadeh A, Kalankesh L. A scope of mobile health solutions in COVID-19 pandemics. Informatics in Medicine Unlocked 2021;23:100558 View
  10. Ikerionwu C, Ugwuishiwu C, Okpala I, James I, Okoronkwo M, Nnadi C, Orji U, Ebem D, Ike A. Application of machine and deep learning algorithms in optical microscopic detection of Plasmodium: A malaria diagnostic tool for the future. Photodiagnosis and Photodynamic Therapy 2022;40:103198 View
  11. Morais M, Silva D, Milagre M, Oliveira M, Pereira T, Silva J, Costa L, Minoprio P, Junior R, Gazzinelli R, de Lana M, Nakaya H. Automatic detection of the parasite Trypanosoma cruzi in blood smears using a machine learning approach applied to mobile phone images. PeerJ 2022;10:e13470 View
  12. Marletta S, L’Imperio V, Eccher A, Antonini P, Santonicco N, Girolami I, Dei Tos A, Sbaraglia M, Pagni F, Brunelli M, Marino A, Scarpa A, Munari E, Fusco N, Pantanowitz L. Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases. Pathology - Research and Practice 2023;243:154362 View
  13. Chibi M, Wasswa W, Ngongoni C, Baba E, Kalu A. Leveraging innovation technologies to respond to malaria: a systematized literature review of emerging technologies. Malaria Journal 2023;22(1) View
  14. Maturana C, de Oliveira A, Nadal S, Bilalli B, Serrat F, Soley M, Igual E, Bosch M, Lluch A, Abelló A, López-Codina D, Suñé T, Clols E, Joseph-Munné J. Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review. Frontiers in Microbiology 2022;13 View
  15. Aris T, Nasir A, Mustafa W, Mashor M, Haryanto E, Mohamed Z. Robust Image Processing Framework for Intelligent Multi-Stage Malaria Parasite Recognition of Thick and Thin Smear Images. Diagnostics 2023;13(3):511 View
  16. Santos-Luna R, Román-Pérez S, Reyes-Cabrera G, Sánchez-Arcos M, Correa-Morales F, Pérez-Solano M. Web Geographic Information System: A Support Tool for the Study, Evaluation, and Monitoring of Foci of Malaria Transmission in Mexico. International Journal of Environmental Research and Public Health 2023;20(4):3282 View
  17. Karageorgos G, Andreadis I, Psychas K, Mourkousis G, Kiourti A, Lazzi G, Nikita K. The Promise of Mobile Technologies for the Health Care System in the Developing World: A Systematic Review. IEEE Reviews in Biomedical Engineering 2019;12:100 View
  18. Shambhu S, Koundal D, Das P, Hoang V, Tran-Trung K, Turabieh H, Hu Z. Computational Methods for Automated Analysis of Malaria Parasite Using Blood Smear Images: Recent Advances. Computational Intelligence and Neuroscience 2022;2022:1 View
  19. Geldsetzer P, Flores S, Wang G, Flores B, Rogers A, Bunker A, Chang A, Tisdale R. A Systematic Review of Healthcare Provider-Targeted Mobile Applications to Screen for, Diagnose, or Monitor Non-Communicable Diseases in Low- and Middle-Income Countries. SSRN Electronic Journal 2021 View
  20. Malhotra K, Wong B, Lee S, Franco H, Singh C, Cabrera Silva L, Iraqi H, Sinha A, Burger S, Breedt D, Goyal K, Dagli M, Bawa A. Role of Artificial Intelligence in Global Surgery: A Review of Opportunities and Challenges. Cureus 2023 View
  21. Park Y, Kang M, Kim Y, Park K, Choi Y. 아프리카 보건의료 분야 특성 분석 및 한국의 개발협력 방안 (Analysis of the Healthcare Sector in Africa and its Policy Implication for Korea). SSRN Electronic Journal 2021 View
  22. Wang G, Luo G, Lian H, Chen L, Wu W, Liu H. Application of Deep Learning in Clinical Settings for Detecting and Classifying Malaria Parasites in Thin Blood Smears. Open Forum Infectious Diseases 2023;10(11) View
  23. Nisworo S, Prananda A. A Review on Digital Microscopic Images for Plasmodium Parasite Detection. TEKNIK 2023;44(3):222 View
  24. Dantas de Oliveira A, Rubio Maturana C, Zarzuela Serrat F, Carvalho B, Sulleiro E, Prats C, Veiga A, Bosch M, Zulueta J, Abelló A, Sayrol E, Joseph-Munné J, López-Codina D, Lopes A. Development of a low-cost robotized 3D-prototype for automated optical microscopy diagnosis: An open-source system. PLOS ONE 2024;19(6):e0304085 View
  25. Alsulimani A, Akhter N, Jameela F, Ashgar R, Jawed A, Hassani M, Dar S. The Impact of Artificial Intelligence on Microbial Diagnosis. Microorganisms 2024;12(6):1051 View
  26. Hamid M, Mohamed A, Mohammed F, Elaagip A, Mustafa S, Elfaki T, Jebreel W, Albsheer M, Dittrich S, Owusu E, Yerlikaya S. Diagnostic accuracy of an automated microscope solution (miLab™) in detecting malaria parasites in symptomatic patients at point-of-care in Sudan: a case–control study. Malaria Journal 2024;23(1) View
  27. Grignaffini F, Simeoni P, Alisi A, Frezza F. Computer-Aided Diagnosis Systems for Automatic Malaria Parasite Detection and Classification: A Systematic Review. Electronics 2024;13(16):3174 View

Books/Policy Documents

  1. Dantas Oliveira A, Carvalho B, Prats C, Espasa M, Gomez i Prat J, Lopez Codina D, Albuquerque J. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. View
  2. Yang F, Yu H, Silamut K, Maude R, Jaeger S, Antani S. Machine Learning in Medical Imaging. View
  3. Vayena E, Feretti A. Global Health. View
  4. Parsa A, Hakkim S, Vinnakota D, Mahmud I, Bulsari S, Dehghani L, Pulikkottil A, Sivasubramanian M, Kabir R. Artificial Intelligence in Medical Virology. View