Estimating the Pile Settlement Using a Machine Learning Technique Optimized by Henry's Gas Solubility Optimization and Particle Swarm Optimization by Saravana Kumar, Savarimuthu Robinson

Subjects: Get full text

Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study by Guo-kang Sun, Yun-hui Xiang, Lu Wang, Pin-pin Xiang, Zi-xin Wang, Jing Zhang, Ling Wu

Subjects: Get full text

Remote sensing assessment of dam impact on arid basins in Southern Saudi Arabia: A machine learning and space-for-time approach by Raid Almalki, Mehdi Khaki, Patricia M. Saco, Jose F. Rodriguez

Subjects: Get full text

A machine learning framework for exploring the relationship between supply chain management best practices and agility, risk management, and performance by Tyler Ward, Sam Khoury, Selva Staub, Kouroush Jenab

Get full text

Evaluation of Machine Learning Algorithms for Classification of Visual Stimulation-Induced EEG Signals in 2D and 3D VR Videos by Mingliang Zuo, Xiaoyu Chen, Li Sui

Subjects: “…machine learning…”
Get full text

Analisis Perbandingan Algoritma Machine Learning dan Deep Learning untuk Klasifikasi Citra Sistem Isyarat Bahasa Indonesia (SIBI) by Mohammad Farid Naufal, Selvia Ferdiana Kusuma

“…Pada penelitian sebelumnya belum ada yang melakukan perbandingan algoritma klasifikasi machine learning dan deep learning untuk pengenalan SIBI. …”
Get full text

Comparison of Resampling Methods and Radiomic Machine Learning Classifiers for Predicting Bone Quality Using Dual-Energy X-Ray Absorptiometry by Mailen Gonzalez, José Manuel Fuertes García, María Belén Zanchetta, Rubén Abdala, José María Massa

Subjects: Get full text

Machine Learning-Based Prediction of 2 MW Wind Turbine Tower Loads During Power Production Based on Nacelle Behavior by Soichiro Kiyoki, Shigeo Yoshida, Mostafa A. Rushdi

Subjects: Get full text

Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy by Lanlan Tang, Wei Zhang, Yang Zhang, Wenjun Deng, Mingyi Zhao

Get full text

Machine learning using random forest to model heavy metals removal efficiency using a zeolite-embedded sheet in water by N.D. Takarina, N. Matsue, E. Johan, A. Adiwibowo, M.F.N.K. Rahmawati, S.A. Pramudyawardhani, T. Wukirsari

“…For developing the zeolite-embedded sheet, the methods include fabrication of the zeolite-embedded sheet using a heating procedure and heavy metals adsorption treatment using the zeolite-embedded sheet. The machine learning analysis to model the heavy metal removal efficiency using zeolite-embedded sheet was performed using the random forest method. …”
Get full text

Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework by Mingyue Xue, Yinxia Su, Chen Li, Shuxia Wang, Hua Yao

“…Combined with the risk factors selected by LR, we used a decision tree, a random forest, AdaBoost with a decision tree (AdaBoost), and an extreme gradient boosting decision tree (XGBoost) to identify individuals with T2DM, compared the performance of the four machine learning classifiers, and used the best-performing classifier to output the degree of variables’ importance scores of T2DM. …”
Get full text

A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment. by Tao Yu, Wei Huang, Xin Tang, Duosi Zheng

Get full text

Development of a New Modified Sonar Inspired Optimization based on Machine Learning Methods for Evaluating Compressive of High-Performance Concrete by Ali Nikkhoo, Amin Moshtagh, Mehri Mehrnia

Get full text

A Practical Approach for Predicting Power in a Small-Scale Off-Grid Photovoltaic System using Machine Learning Algorithms by Aadyasha Patel, O. V. Gnana Swathika, Umashankar Subramaniam, T. Sudhakar Babu, Alok Tripathi, Samriddha Nag, Alagar Karthick, M. Muhibbullah

“…The results are been compared with results obtained by another machine learning algorithm such as polynomial regression and case-based reasoning. …”
Get full text

Machine learning analysis of cervical balance in early-onset scoliosis post-growing rod surgery: a case-control study by Bo Han, Junrui Jonathan Hai, Aixing Pan, Yingjie Wang, Yong Hai

Subjects: Get full text

A Cloud-Based Optimized Ensemble Model for Risk Prediction of Diabetic Progression—An Azure Machine Learning Perspective by V. K. Daliya, T. K. Ramesh

Subjects: Get full text

Application of functional near-infrared spectroscopy and machine learning to predict treatment response after six months in major depressive disorder by Cyrus Su Hui Ho, Jinyuan Wang, Gabrielle Wann Nii Tay, Roger Ho, Hai Lin, Zhifei Li, Nanguang Chen

“…This study investigates whether functional near-infrared spectroscopy (fNIRS) and clinical assessment information can predict treatment response in major depressive disorder (MDD) through machine-learning techniques. Seventy patients with MDD were included in this 6-month longitudinal study, with the primary treatment outcome measured by changes in the Hamilton Depression Rating Scale (HAM-D) scores. fNIRS and clinical information were strictly evaluated using nested cross-validation to predict responders and non-responders based on machine-learning models, including support vector machine, random forest, XGBoost, discriminant analysis, Naïve Bayes, and transformers. …”
Get full text

Predictive value of machine learning for the progression of gestational diabetes mellitus to type 2 diabetes: a systematic review and meta-analysis by Meng Zhao, Zhixin Yao, Yan Zhang, Lidan Ma, Wenquan Pang, Shuyin Ma, Yijun Xu, Lili Wei

Subjects: Get full text

Interpretable machine learning model for predicting clinically significant prostate cancer: integrating intratumoral and peritumoral radiomics with clinical and metabolic features by Wenjun Zhao, Mengyan Hou, Juan Wang, Dan Song, Yongchao Niu

Subjects: Get full text

Uncertainty Quantification for Machine Learning‐Based Ionosphere and Space Weather Forecasting: Ensemble, Bayesian Neural Network, and Quantile Gradient Boosting by Randa Natras, Benedikt Soja, Michael Schmidt

Subjects: “…machine learning…”
Get full text