Results 131 to 140 of about 35,702 (279)

Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis

Advanced Intelligent Systems, EarlyView.
A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang, Marco Peres, Carlo Bradac, Gil Gonçalves   +3 more
wiley   +1 more source

Toward an Accurate Liver Disease Prediction Based on Two-Level Ensemble Stacking Model

IEEE Access
The difficulty of detecting liver disease at an early stage goes back to its limited number of symptoms. In this study, single and ensemble machine learning (ML) algorithms are applied to the Indian Liver Patient Dataset (ILPD) dataset, and their results,
Marghany Hassan Mohamed, Botheina Hussein Ali, Ahmed Ibrahim Taloba, Ahmad O. Aseeri, Mohamed Abd Elaziz, Shaker El-Sappagah, Nora Mahmoud El-Rashidy   +6 more
doaj   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source

Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism

Annals of Neurology, EarlyView.
Objective Pre‐mortem diagnosis of parkinsonism is often challenging due to atypical presentations, overlapping syndromes, and co‐pathologies. This study aimed to develop a machine learning‐based algorithm predicting neuropathology in parkinsonism using chronological clinical presentations, which has previously been underexplored.
Daisuke Ono, Hiroaki Sekiya, Alexia R. Maier, Neill R. Graff‐Radford, Zbigniew K. Wszolek, Dennis W. Dickson   +5 more
wiley   +1 more source

Deep Stacking Ensemble Learning Applied to Profiling Side-Channel Attacks

Deep Learning is nowadays widely used by security evaluators to conduct side-channel attacks, especially in profiling attacks that allow a supervised learning phase. However, designing an efficient neural network model in a side-channel attack context can be a difficult task that may require a laborious hyperparameterization process.
Llavata, Dorian, Cagli, Eleonora, Eyraud, Rémi, Grosso, Vincent, Bossuet, Lilian   +4 more
openaire   +2 more sources

Lifestyle data-based multiclass obesity prediction with interpretable ensemble models incorporating SHAP and LIME analysis

Scientific Reports
Obesity is a major public health concern. Predicting obesity risk from lifestyle data can guide targeted interventions, but current models remain limited.
Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao   +2 more
doaj   +1 more source

Requirement Dependency Extraction Based on Improved Stacking Ensemble Machine Learning

Mathematics
To address the cost and efficiency issues of manually analysing requirement dependency in requirements engineering, a requirement dependency extraction method based on part-of-speech features and an improved stacking ensemble learning model (P-Stacking ...
Hui Guan, Hang Xu, Lie Cai
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

Diverse Models, United Goal: A Comprehensive Survey of Ensemble Learning

CAAI Transactions on Intelligence Technology
Ensemble learning, a pivotal branch of machine learning, amalgamates multiple base models to enhance the overarching performance of predictive models, capitalising on the diversity and collective wisdom of the ensemble to surpass individual models and ...
Ziwei Fan, Zhiwen Yu, Kaixiang Yang, Wuxing Chen, Xiaoqing Liu, Guojie Li, Xianling Yang, C. L. Philip Chen   +7 more
doaj   +1 more source

StackBRAF: A Large-Scale Stacking Ensemble Learning for BRAF Affinity Prediction. [PDF]

ACS Omega, 2023
Syahid NF, Weerapreeyakul N, Srisongkram T.   +2 more
europepmc   +1 more source