Results 171 to 180 of about 293,301 (286)

Multifactor Risk Stratification for Post‐Transplant Alcohol Relapse Using Abstinence, Psychosocial, and Socioeconomic Factors

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Alcohol relapse after liver transplantation is difficult to predict using abstinence duration alone. We developed a multifactor model integrating abstinence duration, psychosocial risk (SIPAT), and socioeconomic context (AUC 0.70). This approach may support individualized risk assessment and tailored follow‐up intensity; external validation is needed ...
Ayato Obana   +9 more
wiley   +1 more source

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males   +8 more
wiley   +1 more source

A New Multiple Imputation Method for High-Dimensional Neuroimaging Data. [PDF]

open access: yesHum Brain Mapp
Lu T   +5 more
europepmc   +1 more source

Reaction kinetics model in liquid and solid phases and its parameterization for room temperature sodium–sulfur battery

open access: yesAIChE Journal, EarlyView.
Abstract A multipore, multiphase, continuum model is assembled for the first time for room temperature sodium–sulfur (RT Na–S) batteries, with Na+ ion transport and redox reactions in the liquid electrolyte phase and semisolid phase of precipitates softened by the electrolyte solvent, as guided by molecular dynamics simulations in this study ...
Hakeem A. Adeoye   +3 more
wiley   +1 more source

The Challenge of Handling Structured Missingness in Integrated Data Sources

open access: yesAdvanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson   +6 more
wiley   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah   +3 more
wiley   +1 more source

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