Point-of-care, smartphone-based, dual-modality, dual-view, oral cancer screening device with neural network classification for low-resource communities

Oral cancer is a growing health issue in a number of low- and middle-income countries (LMIC), particularly in South and Southeast Asia. The described dual-modality, dual-view, point-of-care oral cancer screening device, developed for high-risk populations in remote regions with limited infrastructur...

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Veröffentlicht in:	PloS one Jg. 13; H. 12; S. e0207493
Hauptverfasser:	Uthoff, Ross D., Song, Bofan, Sunny, Sumsum, Patrick, Sanjana, Suresh, Amritha, Kolur, Trupti, Keerthi, G., Spires, Oliver, Anbarani, Afarin, Wilder-Smith, Petra, Kuriakose, Moni Abraham, Birur, Praveen, Liang, Rongguang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 05.12.2018 Public Library of Science (PLoS)
Schlagworte:	Applications programs Artificial neural networks Bioengineering Cancer Cancer screening Classification Cloud Computing Computer and Information Sciences Data processing Diagnosis Diagnostic tests Early Detection of Cancer - instrumentation Early Detection of Cancer - methods Electronic mail systems Engineering and Technology Fluorescence Health care Health care costs Health risks Humans Image classification LEDs Lesions Light emitting diodes Low income groups Medical diagnosis Medical economics Medical imaging Medical imaging equipment Medical screening Medicine and Health Sciences Methyltestosterone Mobile Applications Morbidity Mortality Mouth cancer Mouth Neoplasms - diagnosis Neural networks Neural Networks, Computer Optical Imaging Optics Oral cancer Oral cavity Point of care testing Point-of-Care Systems Poverty Remote regions Research funding Security devices Sensitivity and Specificity Smart phones Smartphone - instrumentation Smartphones Spectrum analysis Tobacco White light California United States > US Arizona India
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	Oral cancer is a growing health issue in a number of low- and middle-income countries (LMIC), particularly in South and Southeast Asia. The described dual-modality, dual-view, point-of-care oral cancer screening device, developed for high-risk populations in remote regions with limited infrastructure, implements autofluorescence imaging (AFI) and white light imaging (WLI) on a smartphone platform, enabling early detection of pre-cancerous and cancerous lesions in the oral cavity with the potential to reduce morbidity, mortality, and overall healthcare costs. Using a custom Android application, this device synchronizes external light-emitting diode (LED) illumination and image capture for AFI and WLI. Data is uploaded to a cloud server for diagnosis by a remote specialist through a web app, with the ability to transmit triage instructions back to the device and patient. Finally, with the on-site specialist's diagnosis as the gold-standard, the remote specialist and a convolutional neural network (CNN) were able to classify 170 image pairs into 'suspicious' and 'not suspicious' with sensitivities, specificities, positive predictive values, and negative predictive values ranging from 81.25% to 94.94%.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0207493