Results 121 to 130 of about 704,599 (275)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

A Rational Optimization Approach for the Development of a Multiplexed Lateral Flow Immunoassay: Detection of Nonepithelial Ovarian Cancer Markers in Human Serum

Advanced Science, EarlyView.
This study outlines the developmental pipeline of a multiplexed nanozyme‐based lateral flow immunoassay for the purpose of ovarian germ cell tumor detection. It demonstrates the application of a design of experiments optimization approach for nanozyme probe conjugate development.
Aida Abdelwahed, Carl E. Eskildsen, Luca Panariello, André Shamsabadi, Christy J. Sadler, Edmund H. Wilkes, Federico Galvanin, Yuxi Cheng, Sara Carvalho, Srdjan Saso, Molly M. Stevens   +10 more
wiley   +1 more source

Wild bootstrap versus moment-oriented bootstrap [PDF]

, 1997
We investigate the relative merits of a moment-oriented bootstrap method of Bunke (1997) in comparison with the classical wild bootstrap of Wu (1986) in nonparametric heteroscedastic regression situations. The moment-oriented bootstrap is a wild bootstrap based on local estimators of higher order error moments that are smoothed by kernel smoothers.
openaire   +2 more sources

Improving the Reliability of Bootstrap Tests [PDF]

We first propose procedures for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication.
James G. MacKinnon, Russell Davidson
core  

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Bootstrapping I(1) Data [PDF]

A functional law for an I(1) sample data version of the continuous-path block bootstrap of Paparoditis and Politis (2001) is given. The results provide an alternative demonstration that continuous-path block bootstrap unit root tests are consistent under
Peter C. B. Phillips
core  

Multi‐Omics Insights Into the Mechanisms of Early Muscle Fiber Difference and Transformation Between Lean‐Type and Chinese Indigenous Pigs

Advanced Science, EarlyView.
Multi‐omics analyses uncover breed‐specific cis‐regulatory landscapes and higher‐order chromatin architectural differences that underlie early postnatal muscle fiber divergence in pigs. A super‐enhancer upstream of PPP3CB recruits MEF2C to activate PPP3CB transcription, while the PPP3CB–MEF2C positive feedback loop promotes oxidative muscle fiber ...
Shuailong Zheng, Hainan Wu, Min Liu, Kunpeng Wu, Shuntao Huang, Zulfiqar Ahmed, Lenox Pius, Mengjin Zhu, Dequan Xu   +8 more
wiley   +1 more source

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring

Advanced Science, EarlyView.
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen, Haoyu Wang, Guixin Xu, Yuqin Yuan, Xinmeng Cai, Zhengwu Wei, Dongheng Zhang, Qibin Sun, Tianwei Zhang, Cuntai Guan, Yan Chen   +10 more
wiley   +1 more source

Maximum Likelihood and the Bootstrap for Nonlinear Dynamic Models [PDF]

We provide a unified framework for analyzing bootstrapped extremum estimators of nonlinear dynamic models for heterogeneous dependent stochastic processes.
Halbert White, Sílvia Gonçalves
core  

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source