Results 71 to 80 of about 157,640 (328)

Bayesian hierarchical vector autoregressive models for patient-level predictive modeling.

PLoS ONE, 2018
Predicting health outcomes from longitudinal health histories is of central importance to healthcare. Observational healthcare databases such as patient diary databases provide a rich resource for patient-level predictive modeling.
Feihan Lu, Yao Zheng, Harrington Cleveland, Chris Burton, David Madigan   +4 more
doaj   +1 more source

Methods for analyzing cost effectiveness data from cluster randomized trials

Cost Effectiveness and Resource Allocation, 2007
Background Measurement of individuals' costs and outcomes in randomized trials allows uncertainty about cost effectiveness to be quantified. Uncertainty is expressed as probabilities that an intervention is cost effective, and confidence intervals of ...
Clark Allan, Fairall Lara, Bachmann Max O, Mugford Miranda   +3 more
doaj   +1 more source

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

Advanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao, Gaiqin Liu, Jingyi Xia, Runle Chen, Tong Wang, Xiaoling Yang, Ruiling Fang, Yanhong Luo, Ping Zeng, Hongmei Yu, Yanbo Zhang, Yuehua Cui   +11 more
wiley   +1 more source

A Stochastic Hybrid Framework for Driver Behavior Modeling Based on Hierarchical Dirichlet Process

, 2018
Scalability is one of the major issues for real-world Vehicle-to-Vehicle network realization. To tackle this challenge, a stochastic hybrid modeling framework based on a non-parametric Bayesian inference method, i.e., hierarchical Dirichlet process (HDP),
Fallah, Yaser P., Mahjoub, Hossein Nourkhiz, Toghi, Behrad   +2 more
core   +1 more source

Steve: A Hierarchical Bayesian Model for Supernova Cosmology [PDF]

The Astrophysical Journal, 2019
Abstract We present a new Bayesian hierarchical model (BHM) named Steve for performing Type Ia supernova (SN Ia) cosmology fits. This advances previous works by including an improved treatment of Malmquist bias, accounting for additional sources of systematic uncertainty, and increasing numerical efficiency.
S. R. Hinton, T. M. Davis, A. G. Kim, D. Brout, C. B. D’Andrea, R. Kessler, J. Lasker, C. Lidman, E. Macaulay, A. Möller, M. Sako, D. Scolnic, M. Smith, R. C. Wolf, M. Childress, E. Morganson, S. Allam, J. Annis, S. Avila, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, C. E. Cunha, L. N. da Costa, C. Davis, J. De Vicente, D. L. DePoy, P. Doel, T. F. Eifler, B. Flaugher, P. Fosalba, J. Frieman, J. García-Bellido, E. Gaztanaga, D. W. Gerdes, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, E. Krause, K. Kuehn, N. Kuropatkin, O. Lahav, M. Lima, M. A. G. Maia, M. March, J. L. Marshall, F. Menanteau, R. Miquel, R. L. C. Ogando, A. A. Plazas, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Soares-Santos, F. Sobreira, E. Suchyta, G. Tarle, D. Thomas, V. Vikram, Y. Zhang   +68 more
openaire   +9 more sources

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

Hierarchical modeling of risk factors with and without prior information—the process of regression model evaluation for an example of respiratory diseases in piglet production from daily practice data

Frontiers in Veterinary Science
In veterinary epidemiology, regression models are commonly used to describe animal health and related risk factors. However, model selection and evaluation present ongoing challenges—especially when many potential predictors, complex interactions, and ...
Timur Tug, Fiona Mers, Franziska Schäkel, Doris Höltig, Lothar Kreienbrock, Katja Ickstadt   +5 more
doaj   +1 more source

Bringing Salary Transparency to the World: Computing Robust Compensation Insights via LinkedIn Salary

, 2017
The recently launched LinkedIn Salary product has been designed with the goal of providing compensation insights to the world's professionals and thereby helping them optimize their earning potential.
Callegaro M., Duerr A., Fielding R. T., Groves R. M., Harris S., Jessen R. J., Job, Sandler R., Statistical Methods SEMATECH, Sumbaly R., Weiner J., Zhang L.   +11 more
core   +1 more source

A hierarchical bayesian model for size recommendation in fashion [PDF]

Proceedings of the 12th ACM Conference on Recommender Systems, 2018
We introduce a hierarchical Bayesian approach to tackle the challenging problem of size recommendation in e-commerce fashion. Our approach jointly models a size purchased by a customer, and its possible return event: 1. no return, 2. returned too small 3. returned too big. Those events are drawn following a multinomial distribution parameterized on the
Romain Guigourès, Yuen King Ho, Evgenii Koriagin, Abdul-Saboor Sheikh, Urs Bergmann, Reza Shirvany   +5 more
openaire   +2 more sources

The Trichinella Super‐Pangenome Reveals the Evolution of Encapsulation and Predicted Host–Parasite Protein Interactions

Advanced Science, EarlyView.
ABSTRACT The muscle capsule of Trichinella is a critical structure that impedes immune attacks and drug penetration, yet the molecular mechanisms underlying its formation remain poorly understood. Using a high‐quality super‐pangenome comprising 12 Trichinella species, we compared extensive genomic variations between encapsulating and non‐encapsulating ...
Qingbo Lv, Yi Liu, Ning Xu, Xiao Zhang, Yaming Yang, Chengyao Li, Hanhai Mao, Mingyuan Liu, Xiaolei Liu   +8 more
wiley   +1 more source