Results 71 to 80 of about 296,811 (276)

A Foundation Model Based CT Biomarker for Non‐Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non‐Small Cell Lung Cancer

Advanced Science, EarlyView.
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu, Shuchang Zhou, Qin Peng, Xiao Bao, Xiaodan Ye, Ahmet Görkem Er, Tong Tong, Mirabela Rusu, Yajia Gu, Mailin Chen, Jing Gong   +10 more
wiley   +1 more source

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

Advanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li, Jialuo Xu, Gaoyuan Du, Xiangting Jia, Dongmin Zhao, Chunyan Zhou, Kexin Xiao, Jia Gu, Junnan Zhu, Xuequn Shang   +9 more
wiley   +1 more source

Scalable Hybrid Deep Models for Individual Pharmacy Cost Prediction

IEEE Access
In this study, we introduce two innovative hybrid models designed for predicting individual pharmacy costs: the Autoencoder-Gated Recurrent Unit (Auto-GRU) and the GoogLeNet-Residual Network (GR-Net).
Muhammad Talha Ashfaq, Nadeem Javaid, Nabil Alrajeh, Yousra Asim, Syed Muhammad Abrar Akber   +4 more
doaj   +1 more source

An Efficient General Family of Estimators for Population Mean in the Presence of Non-Response

Journal of Mathematical and Fundamental Sciences, 2017
This paper presents a new general family of estimators to estimate the population mean of study variable y in the presence of non-response when utilizing a known coefficient of variation of study variable y.
Thanapanang Rachokarn, Nuanpan Lawson
doaj   +1 more source

Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design

Advanced Science, EarlyView.
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng, Chuyi Liu, Zhaoming Liu, Mao Su, Chenyu Tang, Xiang Zheng, Hao Zhang, Jingyuan Li   +7 more
wiley   +1 more source

CPSO-LSTM: Chaotic Particle Swarm Optimization improved LSTM Hyperparameters for Air Pollution Prediction

JOIN: Jurnal Online Informatika
Accurate air pollution predictions are crucial for public health and environmental management, but achieving high prediction accuracy remains a challenge due to the complexity of temporal patterns in pollution data. This study aims to improve performance
Tri Andi, Andri Pranolo, Amelia Ritahani Ismail, Candra Juni Cahyo Kusuma   +3 more
doaj   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Optimal designs for estimation and prediction in simple random-intercept models

上海师范大学学报. 自然科学版, 2013
The paper is concerned with the optimal design problem of estimating linear combinations of the fixed and random effects，and predicting future observations of individual responses in a random intercept model．The variance components in the model are ...
YUE Rongxian, ZHOU Xiaodong
doaj  

Performance evaluation of machine learning algorithms for predicting liquefaction-induced lateral displacement

Scientific Reports
Accurate prediction of liquefaction-induced lateral displacement is essential for seismic risk assessment, resilient infrastructure design, and cost-effective mitigation.
Mahmood Ahmad, Mohammad Al Zubi, Shaikat Biswas, Abdur Rahman Rakib, Abdullah Alzlfawi, Sabahat Hussan, Shay Haq, Rohayu Che Omar, Zia Ullah, Zsolt Tóth   +9 more
doaj   +1 more source

Pressure‐Induced Drift Artifacts in Stretchable Liquid Metal ThinFilm Electrocardiogram Electrodes

Advanced Science, EarlyView.
A stretchable LM electrode integrated with a strain sensor enables in situ quantitative investigation of drift artifact and skin deformation. This reveals the significance of pressure‐induced drift artifact and its intimate relationship with the skin potential model.
Ding Li, Zi‐Gan Xu, Zhi‐Kang Chen, Shuo‐Yan Xu, Jia‐Yi Cui, Si‐Yuan Wo, Zi‐Xu Wang, Yi‐Kun Liu, Jia‐Ju Yin, Hou‐Fang Liu, Xiao‐Ming Wu, Lu‐Qi Tao, Yi Yang, Tian‐Ling Ren   +13 more
wiley   +1 more source