Optimizing Diabetic Foot Ulcer Classification with Transfer Learning: A Performance Analysis

R, Ezhilan and D, Vinod Kumar and P, Umasankar and Suman, Sukhavasi and G, Murali and P, Kowsalikanand (2024) Optimizing Diabetic Foot Ulcer Classification with Transfer Learning: A Performance Analysis. In: UNSPECIFIED.

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Abstract

Diabetic foot ulcers (DFUs) are common in diabetes due to neuropathy and poor circulation, risking severe complications. This study presents a DFU classification approach using transfer learning models: ResNet152, EfficientNetB7, and SE-ResNeXt. EfficientNetB7 achieved highest accuracy (99.65%) and sensitivity (99.8%). ResNet152 had highest specificity (99.8%). Results highlight transfer learning's efficacy for DFU detection, improving diagnostic accuracy and patient outcomes.

Item Type: Conference or Workshop Item (Paper)
Subjects: Engineering > Biomedical Engineering
Divisions: Medicine > Vinayaka Mission's Kirupananda Variyar Medical College and Hospital, Salem > Biochemistry
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 27 Nov 2025 06:46
URI: https://vmuir.mosys.org/id/eprint/1777

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