Effectiveness of the YEARS Algorithm Added to Classical Clinical Decision-making Rules in Suspected Pulmonary Embolism by Handan Özen Olcay, Şeref Kerem Çorbacıoğlu, Emine Emektar, Yunsur Çevik

Get full text

Landslide spatial prediction using data-driven based statistical and hybrid computational intelligence algorithms by Xia Zhao, Wei Chen, Paraskevas Tsangaratos, Ioanna Ilia, Qingfeng He

Get full text

BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

“…All images were annotated with bounding boxes, and the class distribution was relatively balanced to ensure the stability of training and the fairness of evaluation. First, we introduced a Deformable Convolutional Network (DCN) to replace the conventional convolution in the YOLOv10n backbone network, enhancing the model’s adaptability to overlapping leaves, occlusions, and blurred lesion edges. …”
Get full text

Synthetic Data-Based Algorithm Selection for Medical Image Classification Under Limited Data Availability by Maxim Zhabinets, Benjamin Tyler, Martin Lukac, Shinobu Nagayama, Ferdinand Molnár, Michitaka Kameyama

“…Our methodology involves data generation using Generative Adversarial Network. To determine if Algorithm selection trained on synthetically generated data can achieve the same accuracy as if trained on real-world natural data, we systematically evaluate the data generative model using the smallest amount of data needed to choose the right Algorithm and to achieve the expected level of accuracy. …”
Get full text

Conveyor belt deviation identification algorithm based on anchor point positioning and cross-layer correction by Zhe WANG, Zhe FU, Pengjun CAO, Qing LI, Gaoxiang ZHANG

“…Finally, in order to effectively train and evaluate the model performance, 3 268 pictures of various scenes of coal mine underground conveyor belts were collected for training and testing. …”
Get full text

Construction of a prediction model for moderate to severe perimenopausal syndrome based on machine learning algorithms by ZHANG Min, GU Tingting, GUAN Wei, LIU Xiangxiang, SHI Junyao

“…Logistic regression (LR), random forest (RF), support vector machine (SVM), and gradient boosting decision tree (GBDT) were constructed, and model performances were evaluated using accuracy, precision, recall, area under curve(AUC) of the receiver operating characteristic curve, and F1-score.Results A total of 856 perimenopausal women were included in the study, of which 557 were in the normal or mild PMS group and 299 were in the moderate to severe PMS group; 599 were in the training set and 257 were in the testing set. 9 features (employment status, exercise, age, menstrual condition, medical history, obesity, residence area, history of health education, household register) were selected as predictors for the final model using the Boruta algorithm and SHAP analysis. …”
Get full text

Objective Detection of Newborn Infant Acute Procedural Pain Using EEG and Machine Learning Algorithms by Jean‐Michel Roué, Amir Avnit, Behnood Gholami, Wassim M. Haddad, Kanwaljeet J. S. Anand

“…A grid search including five machine learning models was conducted on the training dataset, and each model was evaluated using leave‐one‐subject‐out cross‐validation. …”
Get full text

Optimization of Table Tennis Swing Action Supported by the Temporal Convolutional Network Algorithm in Deep Learning by Shaoxuan Sun, Hongyu Zheng, Zhixin Lin

“…During the experimental phase, the model is evaluated using a dataset of swing actions collected by UAVs, comprising 55,582 data samples, which are divided into training and testing sets in a 3:2 ratio. …”
Get full text

Outliers and anomalies in training and testing datasets for AI-powered morphometry—evidence from CT scans of the spleen by Yuriy Vasilev, Yuriy Vasilev, Anastasia Pamova, Tatiana Bobrovskaya, Anton Vladzimirskyy, Anton Vladzimirskyy, Olga Omelyanskaya, Elena Astapenko, Artem Kruchinkin, Novik Vladimir, Kirill Arzamasov, Kirill Arzamasov

“…IntroductionCreating training and testing datasets for machine learning algorithms to measure linear dimensions of organs is a tedious task. …”
Get full text

Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models by Vasundhara Acharya, Bülent Yener, Gillian Beamer

“…Even non-neural models can learn from a neural network teacher. We evaluated our approach across varying dataset complexities, including the presence or absence of distribution shifts, varying degrees of imbalance, and different levels of graph complexity for training GNNs. …”
Get full text

A Usability Pilot Study of a Sensor-Guided Interactive System for Dexterity Training in Parkinson’s Disease by Nic Krummenacher, Stephan M. Gerber, Manuela Pastore-Wapp, Michael Single, Stephan Bohlhalter, Tobias Nef, Tim Vanbellingen

“…This pilot study aimed to evaluate the usability of a new, feedback-based dexterity training system in people with Parkinson’s disease (PwPD) and healthy adults. …”
Get full text

A Clinical Risk Prediction Model for Depressive Disorders Based on Seven Machine Learning Algorithms by Jin W, Chen S, Wang M, Lin P

“…Univariate logistic regression analysis (p< 0.1) was initially performed to identify potential predictors, followed by feature selection using the Boruta and LASSO algorithms. Seven machine learning algorithms were employed to construct predictive models, with their performance evaluated using metrics such as AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), precision, recall, and F1 score. …”
Get full text

Optimization of Structural Parameters and Mechanical Performance Analysis of a Novel Redundant Actuation Rehabilitation Training Robot by Junyu Wu, He Wang, Yubin Liu, Zhuoqi Man, Xiaofan Yang, Xuanming Cao, Hegao Cai, Jie Zhao

“…The integration of redundant structures into robotic systems enhances the degrees of freedom (DOFs), flexibility, and capability to perform complex tasks. This study evaluates the mechanical performance of a 9-DOF series-parallel hybrid redundant device designed for rehabilitation training of patients with balance disorders. …”
Get full text

Dynamic Response Prediction of Railway Bridges Considering Train Load Duration Using the Deep LSTM Network by Sui Tan, Xiandong Ke, Zhenhao Pang, Jianxiao Mao

“…Monitoring and predicting the dynamic responses of railway bridges under moving trains, including displacement and acceleration, are vital for evaluating the safety and serviceability of the train–bridge system. …”
Get full text

Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…The optimized LightGBM model was trained and evaluated using metrics such as accuracy, precision, and AUC-ROC on the test set, with cross-validation to ensure robustness and generalizability. …”
Get full text

Designing a Stock Recommender System Using the Collaborative Filtering Algorithm for the Tehran Stock Exchange by Marziyeh Nourahmadi, Ali Rahimi, Hojjatollah Sadeqi

“…In the training stage, the algorithm was trained using data from 2012 to 2016, and in the testing stage, its performance was evaluated on data from 2016 to 2021. …”
Get full text

Clustering of ECG Signals Based on Fuzzy Neural Network with Initial Weights Generated by Genetic Algorithm by Elaheh Sayari, Mahdi Yaghoobi

“…Model evaluation results indicate that the proposed model can perform more accurately and less training speed than the conventional statistical methods, a single ANN and FNN. …”
Get full text

Appraising the Pile Settlement Rates by Support Vector Regression Optimized Using the Novel Optimization Algorithms by Argyros Maris

“…Various items are considered to evaluate the movement of the piles that certainly help to understand a future picture of the project over the loading period. …”
Get full text

EfficientNet-b0-Based 3D Quantification Algorithm for Rectangular Defects in Pipelines by Di Wu, Yong Hong, Jie Wang, Shaojun Wu, Zhihao Zhang, Yizhang Liu

“…Quantitative analysis of the magnetic leakage signal is crucial for evaluating the magnitude of pipeline damage after fault detection. …”
Get full text

Modeling Compressive Strength of Self-Compacting Concrete (SCC) Using Novel Optimization Algorithm of AOA by Francisca Blanco, Ye Woo

“…This paper presents a novel approach by combining a Support Vector Machine (SVM) with advanced optimization algorithms to estimate the CS of SCC mixtures accurately. …”
Get full text