Results 201 to 210 of about 49,636 (297)

Missing Confounding Data in Marginal Structural Models: A Comparison of Inverse Probability Weighting and Multiple Imputation

Standard statistical analyses of observational data often exclude valuable information from individuals with incomplete measurements. This may lead to biased estimates of the treatment effect and loss of precision.
Delaney Joseph A.C., Lefebvre Geneviève, Moodie Erica E. M., Platt Robert W   +3 more
core  

Probabilistic retrieval models - relationships, context-specific application, selection and implementation

, 2011
PhDRetrieval models are the core components of information retrieval systems, which guide the document and query representations, as well as the document ranking schemes.
Wang, Jun
core  

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu, Da‐Wen Sun, QingYi Wei, Yibing Zhang, Jidong Tang, Hongbin Pu   +5 more
wiley   +1 more source

Case-mix adjustment through inverse probability weighting to compare health indicators across territories or providers - an application in the agency for health protection of Milan. [PDF]

BMC Health Serv Res
Mazzali C, Andreano A, Magnoni P, Salvatori A, Testa D, Milanese A, Zanfino A, Russo AG.   +7 more
europepmc   +1 more source

Influence of Morphometry on Echocardiographic Measurements in Cavalier King Charles Spaniels: An Inverse Probability Weighting Analysis. [PDF]

Vet Sci, 2021
Bagardi M, Ghilardi S, Locatelli C, Bionda A, Polli M, Bussadori CM, Colombo FM, Pazzagli L, Brambilla PG.   +8 more
europepmc   +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

Sex-based differences in inflammatory predictors of outcomes in patients undergoing mechanical thrombectomy: an inverse probability weighting analysis. [PDF]

Ther Adv Neurol Disord
Prandin G, Foschi M, Valente M, Zhang L, Malhotra P, Sacco S, Ornello R, Toraldo F, Maisano D, Del Regno C, Komauli F, Gartner Jarmillo A, Al-Karadsheh H, Zahid H, Klein P, Abdalkader M, Manganotti P, Lobotesis K, Nguyen TN, Gigli GL, Banerjee S, Merlino G, D'Anna L.   +22 more
europepmc   +1 more source

Comparing the effectiveness of a brief intervention to reduce unhealthy alcohol use among adult primary care patients with and without depression: A machine learning approach with augmented inverse probability weighting. [PDF]

Drug Alcohol Depend, 2022
Papini S, Chi FW, Schuler A, Satre DD, Liu VX, Sterling SA.   +5 more
europepmc   +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi, Minying Low, Peng Xiu, Kresten Lindorff‐Larsen, Yong Wang   +4 more
wiley   +1 more source

Inverse probability weighting to estimate impacts of hypothetical occupational limits on radon exposure to reduce lung cancer. [PDF]

Am J Epidemiol
Keil AP, Li Y, Lan Q, Bertke S, Daniels RD, Edwards JK, Kelly-Reif K.   +6 more
europepmc   +1 more source