Glomerular Disease Classification and Lesion Identification by Machine Learning.
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DOI: 10.1016/j.bj.2021.08.011
Abstract: BACKGROUND Classification of glomerular diseases and identification of glomerular lesions require careful morphological examination by experienced nephropathologists, which is labor-intensive, time-consuming, and prone to interobserver variability. In this regard, recent advance in machine learning-based image… read more here.
Keywords: classification; machine learning; lesion identification; model ... See more keywords