Deep learning classification of urinary sediment crystals with optimal parameter tuning
Abstract The examination of urinary sediment crystals, the sedimentary components of urine, is useful in screening tests, and is always performed in medical examinations. The examination of urinary sediment crystals is typically done by classifying them under a microscope. Although automated analyze...
Main Authors: | Takahiro Nagai, Osamu Onodera, Shujiro Okuda |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-12-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-25385-x |
Similar Items
-
Optimized Parameter Tuning in a Recurrent Learning Process for Shoplifting Activity Classification
by: Ansari Mohd Aquib, et al.
Published: (2023-03-01) -
Optimizing Image Classification: Automated Deep Learning Architecture Crafting with Network and Learning Hyperparameter Tuning
by: Koon Meng Ang, et al.
Published: (2023-11-01) -
Automated urinary sediment detection for Fabry disease using deep-learning algorithms
by: Hidetaka Uryu, et al.
Published: (2022-12-01) -
Hyperparameter Tuning in Deep Learning Approach for Classification of Classical Myeloproliferative Neoplasm
by: Umi Kalsom Mohamad Yusof, et al.
Published: (2022-08-01) -
Small-Sample Seabed Sediment Classification Based on Deep Learning
by: Yuxin Zhao, et al.
Published: (2023-04-01)