Development and validation of a prediction model for coronary heart disease risk in depressed patients aged 20 years and older using machine learning algorithms by Yicheng Wang, Yicheng Wang, Yicheng Wang, Chuan-Yang Wu, Hui-Xian Fu, Jian-Cheng Zhang, Jian-Cheng Zhang, Jian-Cheng Zhang

“…Several evaluation metrics were employed to assess and compare the performance of eight different machine learning models, aiming to identify the most effective algorithm for predicting coronary heart disease risk in individuals with depression. …”
Get full text

Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures by Valerio Zippo, Elisa Robotti, Daniele Maestri, Pietro Fossati, David Valenza, Stefano Maggi, Gennaro Papallo, Masho Hilawie Belay, Simone Cerruti, Giorgio Porcu, Emilio Marengo

“…The proposed approach has a comprehensive connotation, starting from data pre-treatment and cleaning, to model building and prediction. Different machine learning algorithms are compared (Polynomial Regression, LASSO, Random Forests and Gradient Boosting, ANN, SVM, and k-NN), to provide the best predictive ability, also exploiting human reinforcement. …”
Get full text

Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems by Mohamed Medani, Ghada Moh. Samir Elhessewi, Mohammed Alqahtani, Somia A. Asklany, Sulaiman Alamro, Da’ad Albalawneh, Menwa Alshammeri, Mohammed Assiri

Subjects: Get full text

A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases by Norma Latif Fitriyani, Muhammad Syafrudin, Nur Chamidah, Marisa Rifada, Hendri Susilo, Dursun Aydin, Syifa Latif Qolbiyani, Seung Won Lee

“…This research presents a novel prediction model for CVDs utilizing a bagging algorithm that incorporates histogram gradient boosting as the estimator. …”
Get full text

A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

“…A machine learning approach using XGBoost, optimized with the Chaos Game algorithm (CGO-XGBoost), was employed to predict Kc. …”
Get full text

Schools as Citizenship Laboratories in the Digital Era: A Literature Review by Achmad Robi Afrilihadi, Tjipto Sumadi, Nadiroh Nadiroh

Subjects: Get full text

Methods for Cognitive Diagnosis of Students’ Abilities Based on Keystroke Features by Xu Chi, Xinyu Guo, Yu Sheng

Subjects: Get full text

Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
Get full text

Accurate Prediction of 327 Rice Variety Growth Period Based on Unmanned Aerial Vehicle Multispectral Remote Sensing by Zixuan Qiu, Hao Liu, Lu Wang, Shuaibo Shao, Can Chen, Zijia Liu, Song Liang, Cai Wang, Bing Cao

“…In this study, multispectral images of rice at various growth stages were captured using an unmanned aerial vehicle, and single-plant rice silhouettes were identified for 327 rice varieties by establishing a deep-learning algorithm. A growth stage prediction method was established for the 327 rice varieties based on the normalized vegetation index combined with cubic polynomial regression equations to simulate their growth changes, and it was first proposed that the growth stages of different rice varieties were inferred by analyzing the normalized difference vegetation index growth rate. …”
Get full text

Research on prediction of bottom hole flowing pressure for vertical coalbed methane wells based on improved SSA-BPNN by YU Yang, DONG Yintao, LI Yunbo, BAO Yu, ZHANG Lixia, SUN Hao

Subjects: “…|coalbed methane|sparrow search algorithm|neural network|bottom hole flowing pressure|prediction model…”
Get full text

Investigation of an Optimized Linear Regression Model with Nonlinear Error Compensation for Tool Wear Prediction by Lihua Shen, Baorui Du, He Fan, Hailong Yang

Subjects: “…tool wear prediction…”
Get full text

Research on Oil and Gas-Bearing Zone Prediction and Identification Based on the SVD–K-Means Algorithm—A Case Study of the WZ6-1 Oil-Bearing Structure in the Beibu Gulf Basin, South China Sea by Zhilong Chen, Renyi Wang, Biao Xu, Jianghang Zhu

Subjects: Get full text

Adaptive Threshold Algorithm for Outlier Elimination in 3D Topography Data of Metal Additive Manufactured Surfaces Obtained from Focus Variation Microscopy by Xin Xu, Tobias Pahl, Sebastian Hagemeier, Peter Lehmann

Get full text

Research on Path-Following Technology of a Single-Outboard-Motor Unmanned Surface Vehicle Based on Deep Reinforcement Learning and Model Predictive Control Algorithm by Bin Cui, Yuanming Chen, Xiaobin Hong, Hao Luo, Guanqiao Chen

“…This paper proposes a path-tracking control method for a single-outboard-motor USV based on a Deep Deterministic Policy Gradient (DDPG) algorithm and model predictive control (MPC) algorithm. …”
Get full text

IoT-enhanced music therapy: Utilizing genetic algorithms for personalized violin instruction and mental health adjustment by Yuan Wang

Subjects: Get full text

Deep convolutional neural network based archimedes optimization algorithm for heart disease prediction based on secured IoT enabled health care monitoring system by Sureshkumar S, Santhosh Babu A. V, Joseph James S, Maranco M

Subjects: “…Heart disease prediction…”
Get full text

Predicting Rolling Element Bearings’ Deterioration Vibration Trend based on Limited Historical Data for a Desired Confidence Level using Machine Learning Algorithms by Mohammad Reza Seif, Somaye Mohammadi, Parham Rahimi, Mehdi Behzad

Get full text

Advancing flood susceptibility prediction: A comparative assessment and scalability analysis of machine learning algorithms via artificial intelligence in high‐risk regions of Pakistan by Mirza Waleed, Muhammad Sajjad

Get full text

Prediction of 5-year postoperative survival and analysis of key prognostic factors in stage III colorectal cancer patients using novel machine learning algorithms by Wei Zhang, Yan Li, Jinghan Jia, Yuhang Yang, Yuyuan Hu, Yanhong Wang, Jinxi Wang

“…ObjectiveThis study explores the predictive value of clinical and socio-demographic characteristics for postoperative survival in stage III colorectal cancer (CRC) patients and develops a 5-year postoperative survival prediction model using machine learning algorithms.MethodsData from 13,855 stage III CRC patients who underwent surgery were extracted from the SEER database. …”
Get full text

Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma by Ji Zhang, Qing Chen, Yu Zhang, Jie Zhou

“…The present study aims to investigate the efficacy of the random survival forest (RSF) model, which is a machine learning algorithm, in predicting the early postoperative recurrence of HCC, and compare its performance with that of the traditional CPH model. …”
Get full text