Results 201 to 210 of about 1,429,068 (340)

AI‐Driven Defecation Analysis by Smart Healthcare Toilet: Exploring Biometric Patterns and Eu‐Tenesmus

Advanced Science, EarlyView.
A healthcare toilet system is introduced to passively measure defecation behavior. Real‐time data on stool dropping duration, thickness, and a newly defined “eu‐tenesmus” interval show correlations with stool form and gender differences. Results from 45 defecation events reveal a promising method for comprehensive defecation analysis.
Zhiquan Song, TaeHyung Kwon, Jeung Lee, Daeyoun D. Won, Brian J. Lee, Hyuk Soon Choi, Joseph C. Liao, Walter G. Park, Irene Sonu, Stephan Rogalla, Michael J. Rosen, David L. Hu, Jonathan Kuang Ziyang, Sunny Hei Wong, Bong Hyun Jun, Soh Kim, Seung‐min Park   +16 more
wiley   +1 more source

Quantized Convolutional Neural Networks Robustness under Perturbation. [PDF]

F1000Res
Langille J, Hammad I, Kember G.
europepmc   +1 more source

Dermatologist-level classification of skin cancer with deep neural networks

Nature, 2017
A. Esteva, Brett Kuprel, R. Novoa, J. Ko, S. Swetter, H. Blau, S. Thrun   +6 more
semanticscholar   +1 more source

Targeted Intervention Strategies for Maternal–Offspring Transmission of Christensenellaceae in Pigs via a Deep Learning Model

Advanced Science, EarlyView.
This study deciphers maternal‐driven microbial transmission in pigs using a deep learning model (maternal–offspring microbial transmission model), identifying Christensenellaceae R‐7 group as a key transmitted taxon. Filtered galacto‐oligosaccharides‐targeted Christensenellaceae R‐7 group alters offspring microbial functions via maternal ...
Haibo Shen, Xiaokang Ma, Longlin Zhang, Hao Li, Jichang Zheng, Shengru Wu, Ke Zuo, Yulong Yin, Jing Wang, Bie Tan   +9 more
wiley   +1 more source

Design of Novel Auxetic Bi-Materials Using Convolutional Neural Networks. [PDF]

Materials (Basel)
Coropețchi IC, Constantinescu DM, Vasile A, Indreș AI, Sorohan Ș.   +4 more
europepmc   +1 more source

Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks

IEEE Transactions on Geoscience and Remote Sensing, 2016
Yushi Chen, Hanlu Jiang, Chunyang Li, X. Jia, Pedram Ghamisi   +4 more
semanticscholar   +1 more source

A Dynamic Contrast‐Enhanced MRI‐Based Vision Transformer Model for Distinguishing HER2‐Zero, ‐Low, and ‐Positive Expression in Breast Cancer and Exploring Model Interpretability

Advanced Science, EarlyView.
This study develops a Vision Transformer‐based DCE‐MRI model for the non‐invasive classification of HER2 expression in breast cancer, demonstrating robust performance across multicenter cohorts. By integrating transcriptomic analysis, the model reveals immune‐related pathway differences among distinct HER2 expression levels.
Xu Zhang, Yi‐Yuan Shen, Guan‐Hua Su, Yuan Guo, Ren‐Cheng Zheng, Si‐Yao Du, Si‐Yi Chen, Yi Xiao, Zhi‐Ming Shao, Li‐Na Zhang, He Wang, Yi‐Zhou Jiang, Ya‐Jia Gu, Chao You   +13 more
wiley   +1 more source

Automated classification of midpalatal suture maturation using 2D convolutional neural networks on CBCT scans. [PDF]

Front Dent Med
Nik Ravesh M, Ameli N, Lagravere Vich M, Lai H.   +3 more
europepmc   +1 more source

Temporal Convolutional Neural Networks for Diagnosis from Lab Tests

, 2015
Narges Razavian, David Sontag
openalex   +2 more sources

Vehicle Color Recognition in The Surveillance with Deep Convolutional Neural Networks [PDF]

, 2015
Boyang Su, Jie Shao, Jianying Zhou, Xiaoteng Zhang, Lin Mei   +4 more
openalex   +1 more source