Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
A deep learning-based approach to enhance accuracy and feasibility of long-term high-resolution manometry examinations
0
Zitationen
5
Autoren
2025
Jahr
Abstract
Our findings demonstrate that deep learning-based approaches to analyze LTHRM examinations are capable of providing a more reliable and efficient diagnostic process, ultimately making LTHRM assessments more feasible in clinical care.
Ähnliche Arbeiten
A survey on deep learning in medical image analysis
2017 · 13.595 Zit.
Dermatologist-level classification of skin cancer with deep neural networks
2017 · 13.204 Zit.
A survey on Image Data Augmentation for Deep Learning
2019 · 11.823 Zit.
QuPath: Open source software for digital pathology image analysis
2017 · 8.202 Zit.
Radiomics: Images Are More than Pictures, They Are Data
2015 · 8.026 Zit.