Deep learning for diabetes: a systematic review

T Zhu, K Li, P Herrero… - IEEE Journal of Biomedical …, 2020 - ieeexplore.ieee.org
Diabetes is a chronic metabolic disorder that affects an estimated 463 million people
worldwide. Aiming to improve the treatment of people with diabetes, digital health has been …

Early detection of diabetic peripheral neuropathy: a focus on small nerve fibres

J Burgess, B Frank, A Marshall, RS Khalil, G Ponirakis… - Diagnostics, 2021 - mdpi.com
Diabetic peripheral neuropathy (DPN) is the most common complication of both type 1 and 2
diabetes. As a result, neuropathic pain, diabetic foot ulcers and lower-limb amputations …

CS2-Net: Deep learning segmentation of curvilinear structures in medical imaging

L Mou, Y Zhao, H Fu, Y Liu, J Cheng, Y Zheng… - Medical image …, 2021 - Elsevier
Automated detection of curvilinear structures, eg, blood vessels or nerve fibres, from medical
and biomedical images is a crucial early step in automatic image interpretation associated to …

Enhancing self-management in type 1 diabetes with wearables and deep learning

T Zhu, C Uduku, K Li, P Herrero, N Oliver… - npj Digital …, 2022 - nature.com
People living with type 1 diabetes (T1D) require lifelong self-management to maintain
glucose levels in a safe range. Failure to do so can lead to adverse glycemic events with …

Diabetic corneal neuropathy

H Mansoor, HC Tan, MTY Lin, JS Mehta… - Journal of clinical …, 2020 - mdpi.com
Diabetic keratopathy (DK) is a common, but underdiagnosed, ocular complication of
diabetes mellitus (DM) that has a significant economic burden. It is characterised by …

Prevalence of peripheral neuropathy in pre-diabetes: a systematic review

V Kirthi, A Perumbalath, E Brown, S Nevitt… - BMJ Open Diabetes …, 2021 - drc.bmj.com
There is growing evidence of excess peripheral neuropathy in pre-diabetes. We aimed to
determine its prevalence, including the impact of diagnostic methodology on prevalence …

Deep learning for identifying corneal diseases from ocular surface slit-lamp photographs

H Gu, Y Guo, L Gu, A Wei, S Xie, Z Ye, J Xu, X Zhou… - Scientific reports, 2020 - nature.com
To demonstrate the identification of corneal diseases using a novel deep learning algorithm.
A novel hierarchical deep learning network, which is composed of a family of multi-task multi …

Early detection of cardiovascular autonomic neuropathy: A multi-class classification model based on feature selection and deep learning feature fusion

MR Hassan, S Huda, MM Hassan, J Abawajy… - Information …, 2022 - Elsevier
The conventional diagnostic process and tools of cardiovascular autonomic neuropathy
(CAN) can easily identify the two main categories of the condition: severe/definite CAN and …

Artificial intelligence utilising corneal confocal microscopy for the diagnosis of peripheral neuropathy in diabetes mellitus and prediabetes

FG Preston, Y Meng, J Burgess, M Ferdousi, S Azmi… - Diabetologia, 2022 - Springer
Aims/hypothesis We aimed to develop an artificial intelligence (AI)-based deep learning
algorithm (DLA) applying attribution methods without image segmentation to corneal …

Artificial intelligence for diabetes care: current and future prospects

B Sheng, K Pushpanathan, Z Guan, QH Lim… - The Lancet Diabetes & …, 2024 - thelancet.com
Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise
care for people with diabetes and adapt treatments for complex presentations. However, the …