Results 91 to 100 of about 65,886 (196)

The role of artificial intelligence in disease prediction: using ensemble model to predict disease mellitus

Frontiers in Medicine
The traditional complications of diabetes are well known and continue to pose a considerable burden to millions of people with diabetes mellitus (DM). With the continuous accumulation of medical data and technological advances, artificial intelligence ...
Qinyuan Du, Dongli Wang, Yimin Zhang
doaj   +1 more source

Stacking Ensemble Learning Model for Intrusion Detection in Electrical Substation

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Electrical substations are crucial infrastructure in power transmission and distribution but are increasingly vulnerable to cyber threats. However, existing intrusion detection systems (IDS) face challenges such as high false positive rates, limited ...
Mohammad Mahruf Alam, Feddy Setio Pribadi, Rizky Ajie Aprilianto, Arvina Rizqi Nurul’aini   +3 more
doaj   +1 more source

Comprehensive Performance Assessment of Multi-Neural Ensemble Model for Mortality Prediction in ICU

IEEE Access
The development of models to estimate the mortality rate of critically ill patients in the intensive care unit(ICU) is significantly enhanced by technologies based on artificial intelligence.
M. Fathima Begum, Subhashini Narayan
doaj   +1 more source

Comparative Analysis of Voting and Stacking Ensemble Learning for Heart Disease Prediction: A Machine Learning Approach

Jurnal Teknologi Informatika & Komputer
Heart disease remains a leading cause of mortality worldwide, necessitating the development of accurate predictive models for early diagnosis and intervention. This study investigates the effectiveness of ensemble learning approaches, particularly Voting
Gregorius Airlangga
doaj   +1 more source

Thaw Slump Susceptibility Mapping Based on Sample Optimization and Ensemble Learning Techniques in Qinghai-Tibet Railway Corridor

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Thaw slump susceptibility mapping (TSSM) of Qinghai–Tibet railway corridor (QTRC) is the prerequisite and basis for disaster assessment and prevention of permafrost projects.
Yi He, Tianbao Huo, Binghai Gao, Qing Zhu, Long Jin, Jian Chen, Qing Zhang, Jiapeng Tang   +7 more
doaj   +1 more source

Func-Bagging: An Ensemble Learning Strategy for Improving the Performance of Heterogeneous Anomaly Detection Models

Applied Sciences
In the field of ensemble learning, bagging and stacking are two widely used ensemble strategies. Bagging enhances model robustness through repeated sampling and weighted averaging of homogeneous classifiers, while stacking improves classification ...
Ruinan Qiu, Yongfeng Yin, Qingran Su, Tianyi Guan   +3 more
doaj   +1 more source

Examination of Landslide Susceptibility Modeling Using Ensemble Learning and Factor Engineering

Applied Sciences
Current research lacks an in-depth exploration of ensemble learning and factor engineering applications in regard to landslide susceptibility modeling. In the Three Gorges Reservoir area of China, a region prone to frequent landslides that endanger lives
Lizhou Zhang, Siqiao Ye, Deping He, Linfeng Wang, Weiping Li, Bijing Jin, Taorui Zeng   +6 more
doaj   +1 more source

Ensemble learning with explainable AI for improved heart disease prediction based on multiple datasets

Scientific Reports
Heart disease is one of the leading causes of death worldwide. Predicting and detecting heart disease early is crucial, as it allows medical professionals to take appropriate and necessary actions at earlier stages.
Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao   +2 more
doaj   +1 more source

EEFSA-SECM: an enhanced ensemble feature selection and stacking ensemble classifier to detect Parkinson's disease. [PDF]

Front Neurol
Rajput V, Maheswari N.
europepmc   +1 more source

Predicting electronic properties of molecules: a stacking ensemble model for HOMO and LUMO energy estimation. [PDF]

RSC Adv
Mahmoudi O, Kim MH.
europepmc   +1 more source