Results 171 to 180 of about 29,948 (298)

Factors associated with university student dropout: Systematic Review

Introduction: Higher education plays an essential role in social and economic development by promoting equity, well-being, and social mobility. However, university dropout rates, exacerbated by factors such as socioeconomic inequality and the pandemic ...
Loor Vinces, Lester Willian
core   +1 more source

Model interpretability on private-safe oriented student dropout prediction. [PDF]

PLoS One
Liu H, Mao M, Li X, Gao J.
europepmc   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Dropout, School Performance and Working while in School : An Econometric Model with Heterogeneous Groups [PDF]

We develop an econometric model where the determinants of work while in school, dropout and academic grades are set in the context of two types of high school students: those who favor schooling and those who are more inclined to access rapidly the labor
Nathalie Viennot-Briot, Marcel Dagenais, Claude Montmarquette   +2 more
core  

A PSO weighted ensemble framework with SMOTE balancing for student dropout prediction in smart education systems. [PDF]

Sci Rep
Jain A, Dubey AK, Khan S, Panwar A, Alkhatib M, Alshahrani AM.   +5 more
europepmc   +1 more source

Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns

Advanced Intelligent Discovery, EarlyView.
Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer, André Orth, Robert Wang, Ben Breitung, Simon Schweidler, Jasmin Aghassi‐Hagmann, Markus Reischl   +6 more
wiley   +1 more source

Survival Analysis Approach For Early Prediction Of Student Dropout

, 2015
Retention of students at colleges and universities has long been a concern for educators for many decades. The consequences of student attrition are significant for both students, academic staffs and the overall institution.
Ameri, Sattar
core  

Student dropout prediction through machine learning optimization: insights from moodle log data. [PDF]

Sci Rep
Rebelo Marcolino M, Reis Porto T, Thompsen Primo T, Targino R, Ramos V, Marques Queiroga E, Munoz R, Cechinel C.   +7 more
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source