Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Soft Transducer for Patient’s Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection
38
Zitationen
6
Autoren
2022
Jahr
Abstract
) was developed to manage the entire data flow and facilitate the data fruition; this application also implements an innovative face-detection algorithm that ensures the identity of the patient. The robustness of the proposed soft transducer was validated experimentally on five individuals, who used the system for 30 days. The experimental results demonstrated an accuracy in anomaly detection greater than 93%, with a true positive rate of more than 94%.
Ähnliche Arbeiten
Optical Coherence Tomography
1991 · 13.635 Zit.
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
2016 · 7.341 Zit.
YOLOv3: An Incremental Improvement
2018 · 5.887 Zit.
Diabetic Retinopathy
1974 · 5.618 Zit.
Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis
2014 · 5.153 Zit.