Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning

Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious diseases. However, the high variability in cellphone image data acquisition and the common need for large amounts of specialist-annotated images for tr...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	ACS nano 2021-01, Vol.15 (1), p.665-673
Hauptverfasser:	Shokr, Ahmed, Pacheco, Luis G. C, Thirumalaraju, Prudhvi, Kanakasabapathy, Manoj Kumar, Gandhi, Jahnavi, Kartik, Deeksha, Silva, Filipe S. R, Erdogmus, Eda, Kandula, Hemanth, Luo, Shenglin, Yu, Xu G, Chung, Raymond T, Li, Jonathan Z, Kuritzkes, Daniel R, Shafiee, Hadi
Format:	Artikel
Sprache:	eng
Schlagworte:	Antigens, Viral - isolation & purification Communicable Disease Control COVID-19 - diagnosis COVID-19 Testing - instrumentation COVID-19 Testing - methods CRISPR-Cas Systems Deep Learning Disaster Planning Humans Image Processing, Computer-Assisted - methods Metal Nanoparticles - chemistry Neural Networks, Computer Platinum Point-of-Care Testing Public Health Reproducibility of Results Signal Processing, Computer-Assisted Smartphone Telemedicine - methods
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!