mlsanityData to 14 Oct 2026

A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcers

arXiv 2105.07763 ↗First posted 17 May 2021cs.LG cs.CVcited by 7

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Abstract (arXiv)

This research proposes a mobile and cloud-based framework for the automatic detection of diabetic foot ulcers and conducts an investigation of its performance. The system uses a cross-platform mobile framework which enables the deployment of mobile apps to multiple platforms using a single TypeScript code base. A deep convolutional neural network was deployed to a cloud-based platform where the mobile app could send photographs of patient's feet for inference to detect the presence of diabetic foot ulcers. The functionality and usability of the system were tested in two clinical settings: Salford Royal NHS Foundation Trust and Lancashire Teaching Hospitals NHS Foundation Trust. The benefits of the system, such as the potential use of the app by patients to identify and monitor their condition are discussed.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 3 of its 31 references that are in the map. First posted on arXiv 17 May 2021.

Builds on

3 of 31 references.

References · 3

  1. 2017Fully Convolutional Networks for Diabetic Foot Ulcer Segmentationcited by 17
  2. 2017DFUNet: Convolutional Neural Networks for Diabetic Foot Ulcer Classificationcited by 16
  3. 2020DFUC2020: Analysis Towards Diabetic Foot Ulcer Detectioncited by 6

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Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1; 2025: 1.

7 papers.