Evidence map›Paper›PMID 36578875›Full record

ReviewWorld journal of diabetes2022

The role of artificial intelligence technology in the care of diabetic foot ulcers: the past, the present, and the future.

Joseph M Pappachan, Bill Cassidy, Cornelius James Fernandez, Vishnu Chandrabalan, Moi Hoon Yap

Open access · diamondAbstract readReview
In one paragraph

Review in World journal of diabetes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
6.0field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 44 citations in OpenAlex.

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  11. Artificial Intelligence to Diagnose Complications of Diabetes.Journal of diabetes science and technology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Joseph M PappachanDepartment of Endocrinology & Metabolism, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom.
Bill CassidyFaculty of Science and Engineering, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom.
Cornelius James FernandezDepartment of Endocrinology & Metabolism, Pilgrim Hospital, Boston PE21 9QS, United Kingdom.
Vishnu ChandrabalanDepartment of Data Science, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom.
Moi Hoon YapFaculty of Science and Engineering, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom.
Manchester Metropolitan University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Foot ulcers are common complications of diabetes mellitus and substantially increase the morbidity and mortality due to this disease. Wound care by regular monitoring of the progress of healing with clinical review of the ulcers, dressing changes, appropriate antibiotic therapy for infection and proper offloading of the ulcer are the cornerstones of the management of foot ulcers. Assessing the progress of foot ulcers can be a challenge for the clinician and patient due to logistic issues such as regular attendance in the clinic. Foot clinics are often busy and because of manpower issues, ulcer reviews can be delayed with detrimental effects on the healing as a result of a lack of appropriate and timely changes in management. Wound photographs have been historically useful to assess the progress of diabetic foot ulcers over the past few decades. Mobile phones with digital cameras have recently revolutionized the capture of foot ulcer images. Patients can send ulcer photographs to diabetes care professionals electronically for remote monitoring, largely avoiding the logistics of patient transport to clinics with a reduction on clinic pressures. Artificial intelligence-based technologies have been developed in recent years to improve this remote monitoring of diabetic foot ulcers with the use of mobile apps. This is expected to make a huge impact on diabetic foot ulcer care with further research and development of more accurate and scientific technologies in future. This clinical update review aims to compile evidence on this hot topic to empower clinicians with the latest developments in the field.

Indexed as

Artificial intelligence technologyCOVID-19 pandemicDiabetic foot ulcersDigital photographyMobile appPhotographic monitoring

Identifiers

PMID36578875
PMCPMC9791570
OpenAlexW4311418208

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.