Results 81 to 90 of about 137,972 (308)
Journal of Causal Inference, 2022 Statistical power is often a concern for clustered randomized control trials (RCTs) due to variance inflation from design effects and the high cost of adding study clusters (such as hospitals, schools, or communities).
Schochet Peter Z.
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Arthritis Care &Research, EarlyView.Objective Systemic lupus erythematosus (SLE) is a heterogenous inflammatory condition with widely varying global prevalence estimates. The frequency of SLE in the general population of Australia has been reported to be notably lower than contemporary estimates in countries such as the United States or United Kingdom, at 19 to 39 per 100,000 as opposed ...
Lucinda Roper +7 more
wiley +1 more source
LASSO-based machine learning algorithm to predict the incidence of diabetes in different stages
, 2023 Formal risk assessment is crucial for diabetes prevention. We aimed to establish a practical nomogram for predicting the risk incidence of prediabetes and prediabetes conversion to diabetes.
Huibiao Quan (9338183) +5 more
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Arthritis Care &Research, EarlyView.Objective This research article aims to describe the prevalence, associations, and health‐related quality of life (HRQoL) impact of mucocutaneous features of systemic lupus erythematosus (SLE). Methods Data from the Asia‐Pacific Lupus Collaboration cohort were analyzed (2013–2021).
Amanda M. Saracino +42 more
wiley +1 more source
Cancer Management and Research, 2023 Yichen Wang,1,* Tao Zhou,2,* Shanshan Zhao,1,* Ning Li,3 Siwen Sun,1 Man Li1 1Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People’s Republic of China; 2Department of Oncology, The First ...
Wang Y +5 more
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Multiplicative Updates for the Lasso [PDF]
2007 IEEE Workshop on Machine Learning for Signal Processing, 2007 Multiplicative updates have proven useful for non-negativity constrained optimization. Presently, we demonstrate how multiplicative updates also can be used for unconstrained optimization. This is for instance useful when estimating the least absolute shrinkage and selection operator (LASSO) i.e.
Mørup, Morten, Clemmensen, Line Harder
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Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
An Equivalence between the Lasso and Support Vector Machines [PDF]
We investigate the relation of two fundamental tools in machine learning and signal processing, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression.
Jaggi, Martin
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Advances in Sustainable and Wearable Textile Based Soft Robotics
Advanced Functional Materials, EarlyView.This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas +6 more
wiley +1 more source
A comparative study of the Lasso-type and heuristic model selection methods [PDF]
This study presents a first comparative analysis of Lasso-type (Lasso, adaptive Lasso, elastic net) and heuristic subset selection methods. Although the Lasso has shown success in many situations, it has some limitations.
Ivan Savin
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