2024-12-23-sharma24a.md

title	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
Lupus Nephritis Subtype Classification with only Slide Level Labels	Lupus Nephritis classification has historically relied on labor-intensive and meticulous glomerular-level labeling of renal structures in whole slide images (WSIs). However, this approach presents a formidable challenge due to its tedious and resource-intensive nature, limiting its scalability and practicality in clinical settings. In response to this challenge, our work introduces a novel methodology that utilizes only slide-level labels, eliminating the need for granular glomerular-level labeling. A comprehensive multi-stained lupus nephritis digital histopathology WSI dataset was created from the Indian population, which is the largest of its kind. LupusNet, a deep learning MIL-based model, was developed for the sub- type classification of LN. The results underscore its effectiveness, achieving an AUC score of 91.0%, an F1-score of 77.3%, and an accuracy of 81.1% on our dataset in distinguishing membranous and diffused classes of LN.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	sharma24a	0	Lupus Nephritis Subtype Classification with only Slide Level Labels	1401	1411	1401-1411	1401	false	Sharma, Amit and Chauhan, Ekansh and Uppin, Megha S and Rajasekhar, Liza and Jawahar, C.V. and Vinod, P K	given family Amit Sharma given family Ekansh Chauhan given family Megha S Uppin given family Liza Rajasekhar given family C.V. Jawahar given family P K Vinod	2024-12-23		Proceedings of The 7nd International Conference on Medical Imaging with Deep Learning	250	inproceedings	date-parts 2024 12 23	https://raw.githubusercontent.com/mlresearch/v250/main/assets/sharma24a/sharma24a.pdf