Fast and robust invariant generalized linear models

Fast and robust invariant generalized linear models

<p>Statistical integration of diverse data sources is an essential step in the building of generalizable prediction tools, especially in precision health. The invariant features model is a new paradigm for multi-source data integration which posits that a small number of covariates affect the...

Полное описание

Сохранить в:

Библиографические подробности
Главный автор:	Parker Knight (22683015) (author)
Другие авторы:	Ndey Isatou Jobe (22683018) (author), Rui Duan (561668) (author)
Опубликовано:	2025
Предметы:	Medicine Genetics Molecular Biology Physiology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified data integration optimization electronic health records risk prediction
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!

Схожие документы

Comparative analysis of spike sorting using Uniform Manifold Approximation and Projection (UMAP) vs. feature-based methods in in vivo extracellular recordings.
по: Daniel Suárez-Barrera (22676654)
Опубликовано: (2025)

Spatiotemporal spike sorting on multi-electrode array (MEA) data: Uniform Manifold Approximation and Projection (UMAP) vs. SpyKING CIRCUS (SC).
по: Daniel Suárez-Barrera (22676654)
Опубликовано: (2025)

Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information.
по: Daniel Suárez-Barrera (22676654)
Опубликовано: (2025)

Impact of multiunit merging on neural information encoding.
по: Daniel Suárez-Barrera (22676654)
Опубликовано: (2025)

Comparison of Uniform Manifold Approximation and Projection (UMAP)-based and feature-based spike sorting on synthetic data.
по: Daniel Suárez-Barrera (22676654)
Опубликовано: (2025)

Comparison of feature-based and Uniform Manifold Approximation and Projection (UMAP)-based spike sorting for neuron classification.
по: Daniel Suárez-Barrera (22676654)
Опубликовано: (2025)

Additional file 2 of Machine learning model for predicting severe infection in children with idiopathic nephrotic syndrome: multicenter retrospective study
по: Sijie Yu (8895605)
Опубликовано: (2025)

Additional file 1 of Machine learning model for predicting severe infection in children with idiopathic nephrotic syndrome: multicenter retrospective study
по: Sijie Yu (8895605)
Опубликовано: (2025)

Comprehensive Transformation Robustness Analysis Results.
по: Kewei Wang (556371)
Опубликовано: (2025)

Transformation Robustness Parameter Impact Analysis.
по: Kewei Wang (556371)
Опубликовано: (2025)

Scalability and robustness analysis of the IGA-NSGA-II framework.
по: Kewei Wang (556371)
Опубликовано: (2025)

Plasticity model shows continued linear increases in LTP induction at higher frequencies.
по: Nicholas Hananeia (22683665)
Опубликовано: (2025)

Robustness checks.
по: Yuanbo Hu (10142927)
Опубликовано: (2025)

Robustness of TransMarker concerning the selection and completeness of the prior knowledge network.
по: Fatemeh Keikha (20917848)
Опубликовано: (2025)

Presynaptic and postsynaptic weights change monotonically linearly over stimulus duration.
по: Nicholas Hananeia (22683665)
Опубликовано: (2025)

Entropy-Driven Amino Acid-Based Coacervates with Enzyme-Free Metabolism and Prebiotic Robustness
по: Shuai Cao (775058)
Опубликовано: (2025)

Entropy-Driven Amino Acid-Based Coacervates with Enzyme-Free Metabolism and Prebiotic Robustness
по: Shuai Cao (775058)
Опубликовано: (2025)

Robustness analysis of the entropic regularization parameter in the Gromov–Wasserstein alignment step of TransMarker.
по: Fatemeh Keikha (20917848)
Опубликовано: (2025)

Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
по: Anubhuti Shukla (12152228)
Опубликовано: (2025)

Comparison of algorithm performance under actual coordinate points.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

Comparison of algorithm performance under random coordinate points.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

Simulation parameters for UAV path planning.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

OPTION-A*-DQN algorithm cycle payoff plot.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

OPTION-Dijkstra-DQN algorithm cycle payoff plot.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

Bar chart comparing the return-to-charge frequency before and after optimization for different algorithms.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

(A) Initial path planning result using the OPTION-A*-DQN algorithm.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

(A) Initial path planning result using the OPTION-SA-DQN algorithm.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

(A) Initial path planning result using the OPTION-Dijkstra-DQN algorithm.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

OPTION-DQN algorithm flowchart.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

Flowchart of the intelligent inspection area partitioning algorithm.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

Illustration of dynamic real-time obstacle avoidance.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

(A) The charging process of a UAV returning to the offshore substation for energy replenishment.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

Turbine distribution map of Yangjiang Phase I wind farm.
по: Meiqing Xu (8502255)
Опубликовано: (2025)

Flow diagram of the proposed model.
по: Uğur Ejder (22683228)
Опубликовано: (2025)

The comparison of the accuracy score of the benchmark and the proposed models.
по: Uğur Ejder (22683228)
Опубликовано: (2025)

The prediction accuracy of simple versus hybrid models.
по: Uğur Ejder (22683228)
Опубликовано: (2025)

Top-performing model configuration and performance by algorithm type.
по: Uğur Ejder (22683228)
Опубликовано: (2025)

The accuracy score change matrix following model development.
по: Uğur Ejder (22683228)
Опубликовано: (2025)

Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
по: Uğur Ejder (22683228)
Опубликовано: (2025)

Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction.
по: Uğur Ejder (22683228)
Опубликовано: (2025)

Cannot write session to /tmp/vufind_sessions/sess_0fdesgjclia16vj5ip7p4r29hh