Results 41 to 50 of about 61,068 (254)

An Ensemble of Light Gradient Boosting Machine and Adaptive Boosting for Prediction of Type-2 Diabetes

International Journal of Computational Intelligence Systems, 2023
AbstractMachine learning helps construct predictive models in clinical data analysis, predicting stock prices, picture recognition, financial modelling, disease prediction, and diagnostics. This paper proposes machine learning ensemble algorithms to forecast diabetes. The ensemble combines k-NN, Naive Bayes (Gaussian), Random Forest (RF), Adaboost, and
M. Jishnu Sai, Pratiksha Chettri, Ranjit Panigrahi, Amik Garg, Akash Kumar Bhoi, Paolo Barsocchi   +5 more
openaire   +2 more sources

Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments

Scientific Reports, 2022
Rockburst is a severe geological hazard that restricts deep mine operations and tunnel constructions. To overcome the shortcomings of widely used algorithms in rockburst prediction, this study investigates the ensemble trees, i.e., random forest (RF ...
Diyuan Li, Zida Liu, Danial Jahed Armaghani, Peng Xiao, Jian Zhou   +4 more
doaj   +1 more source

Comparison of Two Methods, Gradient Boosting and Extreme Gradient Boosting to Pre- dict Survival in Covid-19 Data

Journal of Biostatistics and Epidemiology, 2023
Introduction: The present study discusses the importance of having a predictive method to determine the prognosis of patients with diseases like Covid-19.
Nadiasadat Taghavi Razavizadeh, Maryam Salari, Mostafa Jafari, Ehsan Sabaghian, Vahid Ghavami   +4 more
doaj   +1 more source

Strength Estimation and Feature Interaction of Carbon Nanotubes-Modified Concrete Using Artificial Intelligence-Based Boosting Ensembles

Buildings
The standard approach for testing ordinary concrete compressive strength (CS) is to cast samples and test them after different curing times. However, testing adds cost and time to projects, and, therefore, construction sites experience delays.
Fei Zhu, Xiangping Wu, Yijun Lu, Jiandong Huang   +3 more
doaj   +1 more source

DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning

Proceedings of the ACM on Management of Data, 2023
As machine learning (ML) has been widely developed in real-world applications, the privacy of ML models draws an increasing concern. In this paper, we study how to forget specific data records from ML models to preserve the privacy of these data. Although some studies propose efficient unlearning algorithms on random forests and extremely randomized ...
Zhaomin Wu, Junhui Zhu, Qinbin Li, Bingsheng He   +3 more
openaire   +1 more source

The human gut microbiome across the life course

FEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero, Basak Bahcivanci, Antonietta Hayhoe, Animesh Acharjee, Ezgi Özkurt   +4 more
wiley   +1 more source

Extreme Learning Machine Enhanced Gradient Boosting for Credit Scoring

Algorithms, 2022
Credit scoring is an effective tool for banks and lending companies to manage the potential credit risk of borrowers. Machine learning algorithms have made grand progress in automatic and accurate discrimination of good and bad borrowers. Notably, ensemble approaches are a group of powerful tools to enhance the performance of credit scoring.
Yao Zou 0001, Changchun Gao
openaire   +2 more sources

Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu, Jie‐Jie Li, Jing Jing, Jin‐Xi Lin, Xia Meng, Yong Jiang, Yong‐Jun Wang, Hong‐Qiu Gu   +7 more
wiley   +1 more source

Prediction of 5-year overall survival of tongue cancer based machine learning

BMC Oral Health, 2023
Objective We aimed to develop a 5-year overall survival prediction model for patients with oral tongue squamous cell carcinoma based on machine learning methods.
Liangbo Li, Cheng Pu, Nenghao Jin, Liang Zhu, Yanchun Hu, Piero Cascone, Ye Tao, Haizhong Zhang   +7 more
doaj   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source