[HTML][HTML] The Power of Deep Learning Techniques for Predicting Student Performance in Virtual Learning Environments: A Systematic Literature Review

B Alnasyan, M Basheri, M Alassafi - Computers and Education: Artificial …, 2024 - Elsevier
With the advances in Artificial Intelligence (AI) and the increasing volume of online
educational data, Deep Learning techniques have played a critical role in predicting student …

Predicting university student graduation using academic performance and machine learning: a systematic literature review

LR Pelima, Y Sukmana, Y Rosmansyah - IEEE Access, 2024 - ieeexplore.ieee.org
Predicting university student graduation is a beneficial tool for both students and institutions.
With the help of this predictive capacity, students may make well-informed decisions about …

A high ranking-based ensemble network for student's performance prediction using improved meta-heuristic-aided feature selection and adaptive GAN for …

S Punitha, K Devaki - Kybernetes, 2024 - emerald.com
Purpose Predicting student performance is crucial in educational settings to identify and
support students who may need additional help or resources. Understanding and predicting …

Multivariate time-series deep learning for joint prediction of temperature and relative humidity in a closed space

FE Gunawan, AS Budiman, B Pardamean… - Procedia Computer …, 2023 - Elsevier
An accurate predictive model of temperature and humidity plays a vital role in many
industrial processes that utilize a closed space such as in agriculture and building …

[HTML][HTML] SSMFN: a fused spatial and sequential deep learning model for methylation site prediction

FR Lumbanraja, B Mahesworo, TW Cenggoro… - PeerJ Computer …, 2021 - peerj.com
Background Conventional in vivo methods for post-translational modification site prediction
such as spectrophotometry, Western blotting, and chromatin immune precipitation can be …

Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models

K Moulaei, L Afshari, R Moulaei, B Sabet… - Scientific Reports, 2024 - nature.com
Failure to predict stroke promptly may lead to delayed treatment, causing severe
consequences like permanent neurological damage or death. Early detection using deep …

Sequence to sequence deep learning architecture for forecasting temperature and humidity inside closed space

KE Setiawan, GN Elwirehardja… - 2022 10th International …, 2022 - ieeexplore.ieee.org
Solar Dryer Dome (SDD), an agricultural facility for drying and preserving agricultural
products, needs a smart ability to predict the future indoor climate accurately, including …

Multi-level contrastive graph learning for academic abnormality prediction

Y Ouyang, Y Wang, R Gao, Y Zeng, J Liu… - Neural Computing and …, 2024 - Springer
Abstract Academic Abnormality Prediction aims to predict whether students have academic
abnormalities through their historical academic scores. However, existing research methods …

A novel attention-based multi-modal modeling technique on mixed type data for improving TFT-LCD repair process

Y Liu, HP Lu, CH Lai - IEEE Access, 2022 - ieeexplore.ieee.org
In Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) manufacturing, conducting a
machine learning based system with multiple data types has become actively desired to …

An Explainable Decision Support Framework for Differential Diagnosis between Mild COVID-19 and Other Similar Influenzas

K Chadaga, S Prabhu, N Sampathila, R Chadaga… - IEEE …, 2024 - ieeexplore.ieee.org
It is tough to clinically differentiate between mild COVID-19 and other similar influenzas due
to their comparable transmission traits and symptoms. The Real-time reverse transcriptase …