Leprosy Skin Lesion Detection: An AI Approach Using Few Shot Learning in a Small Clinical Dataset

Simple item page
dc.contributor.authorBeesetty, Ren_US
dc.contributor.authorReddy, SAen_US
dc.contributor.authorModali, Sen_US
dc.contributor.authorSunkara, Gen_US
dc.contributor.authorDalal, Jen_US
dc.contributor.authorDamagathla, Jen_US
dc.contributor.authorBanerjee, Den_US
dc.contributor.authorVenkatachalapathy, Men_US
dc.date.accessioned2023-08-09T06:22:35Z
dc.date.available2023-08-09T06:22:35Z
dc.date.issued2023-06
dc.description.abstractThis is an exploratory research study to check if artificial intelligence (AI) based image marker tool can aid leprosy screening to detect leprosy cases early in field situation and reduce the financial and personnel burden. We aimed to collect clinical leprosy skin lesion images and develop an AI model to identify and differentiate them. A total of 368 clinically diagnosed leprosy and 28 non-leprosy skin lesions were collected by an expert leprologist from 151 eligible patients using a multimodal imaging protocol. A Siamese-based Few Shot Learning (FSL) model was trained as it is a meta learning approach on an extremely small data set with fewer disease classes (disease conditions as categories). The number of class labels were increased by fine-grained grouping of skin lesions based on skin morphology (Nine leprosy subgroups) and further divided into train-set and test-set. An AI model was successfully developed, and the results indicated an accuracy of 91.25% and 73.12% on train-set and test-set for two-way one-shot task, respectively. The best sensitivity-specificity for the test-set were 72.39%-73.66% (two-way one-shot task). This early research data indicates that the development of AI based leprosy screening application is feasible using the skin lesion image as marker. The FSL method was successfully used in this training the small data set. However, this is a small sample size study, and more leprosy cases need to be enrolled along with an equal number of non- leprosy cases while improving model architecture to reduce overfit or bias problem. Moreover, as of now this tool cannot be used for neural leprosy (having no skin lesion) as well as lepromatous leprosy having diffuse infiltration. This tool will need further development and validation on pictures taken by different categories of common health care workers using available mobile phones.en_US
dc.identifier.affiliationsNovartis Healthcare Private Limited, Hyderabad-500081, Telangana, Indiaen_US
dc.identifier.affiliationsSivananda Rehabilitation Center, Hyderabad-500081, Telangana, Indiaen_US
dc.identifier.affiliationsNovartis Healthcare Private Limited, Hyderabad-500081, Telangana, Indiaen_US
dc.identifier.affiliationsNovartis Pharmaceuticals Corporation, New Jersey, USAen_US
dc.identifier.affiliationsNovartis Healthcare Private Limited, Hyderabad-500081, Telangana, Indiaen_US
dc.identifier.affiliationsMS , Novartis Healthcare Private Limited, Hyderabad-500081, Telangana, Indiaen_US
dc.identifier.affiliationsM Stat , Novartis Healthcare Private Limited, Hyderabad-500081, Telangana, Indiaen_US
dc.identifier.affiliationsNovartis Healthcare Private Limited, Hyderabad-500081, Telangana, Indiaen_US
dc.identifier.citationBeesetty R, Reddy SA, Modali S, Sunkara G, Dalal J, Damagathla J, Banerjee D, Venkatachalapathy M. Leprosy Skin Lesion Detection: An AI Approach Using Few Shot Learning in a Small Clinical Dataset. Indian Journal of Leprosy. 2023 Jun; 95: 89-102en_US
dc.identifier.issn0254-9395
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/222637
dc.languageenen_US
dc.publisherHind Kusht Nivaran Sangh (Indian Leprosy Association)en_US
dc.relation.volume95en_US
dc.source.urihttps://www.ijl.org.in/article-detail/95/451en_US
dc.subjectApplied Artificial Intelligenceen_US
dc.subjectAIen_US
dc.subjectFew Shot Learningen_US
dc.subjectLeprosy Screeningen_US
dc.subjectSiamese Networken_US
dc.subjectSkin Imagingen_US
dc.titleLeprosy Skin Lesion Detection: An AI Approach Using Few Shot Learning in a Small Clinical Dataseten_US
dc.typeJournal Articleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
IJL2023v95p89.pdf
Size:
1.93 MB
Format:
Adobe Portable Document Format
Download
Collections
Indian Journal of Leprosy