A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot by Xilin Xiao, Xiaojian Li, Hangjie Mo, Yudong Shi, Jing Fang, Ling Li, Bo Ouyang, Shanlin Yang

“…Shared control combines human intelligence with autonomous algorithms, demonstrating potential for enhancing the intricate and dynamic operational capabilities of robots. …”
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Enhancing noninvasive pancreatic cystic neoplasm diagnosis with multimodal machine learning by Wei Huang, Yue Xu, Zhao Li, Jun Li, Qing Chen, Qiang Huang, Yaping Wu, Hongtan Chen

“…The study’s results indicate that our multimodal machine learning algorithm, which integrates both clinical and imaging data, significantly outperforms single-source data algorithms. …”
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Interpretable machine learning modeling of temperature rise in a medium voltage switchgear using multiphysics CFD analysis by Mahmood Matin, Amir Dehghanian, Amir Hossein Zeinaddini, Hossein Darijani

“…Artificial intelligence (AI) algorithms have gained attention in various engineering fields to address similar issues. …”
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Technological Advancements in Human Navigation for the Visually Impaired: A Systematic Review by Edgar Casanova, Diego Guffanti, Luis Hidalgo

“…Current navigation algorithms were also identified in the review with methods including obstacle detection, path planning, and trajectory prediction, applied to technologies such as ultrasonic sensors, RGB-D cameras, and LiDAR for indoor navigation, as well as stereo cameras and GPS for outdoor navigation. …”
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Fractional Optimizers for LSTM Networks in Financial Time Series Forecasting by Mustapha Ez-zaiym, Yassine Senhaji, Meriem Rachid, Karim El Moutaouakil, Vasile Palade

“…We extend several widely used optimization algorithms—including Adam, RMSprop, SGD, Adadelta, FTRL, Adamax, and Adagrad—by incorporating fractional derivatives into their update rules. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…It is presumed that the implementation of deep learning algorithms demands a large amount of data to learn complex features automatically and this can pose a challenge for applications with lesser data to achieve generalization. …”
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Identification of a Hypoxia-Angiogenesis lncRNA Signature Participating in Immunosuppression in Gastric Cancer by Zicheng Wang, Xisong Liang, Hao Zhang, Zeyu Wang, Xun Zhang, Ziyu Dai, Zaoqu Liu, Jian Zhang, Peng Luo, Jiarong Li, Quan Cheng

“…As a result, we found that HARM predicted patient survival with high accuracy and was correlated with higher stages of gastric cancer. …”
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Hybrid Intelligence approach to study post-processing impact on the mechanical performance of notched additively manufactured AlSi10Mg by Erfan Maleki, Sara Bagherifard, Okan Unal, Mario Guagliano

“…In parallel, Artificial Intelligence (AI), utilizing advanced machine learning (ML) algorithms, performed tasks related to prediction, sensitivity analysis, and parametric analysis. …”
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Optimization of clustering parameters for single-cell RNA analysis using intrinsic goodness metrics by Nicolina Sciaraffa, Antonino Gagliano, Luigi Augugliaro, Claudia Coronnello, Claudia Coronnello

“…This procedure has enabled the effective prediction of clustering accuracy through the utilization of intrinsic metrics. …”
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The Performance of an ML-Based Weigh-in-Motion System in the Context of a Network Arch Bridge Structural Specificity by Dawid Piotrowski, Marcin Jasiński, Artur Nowoświat, Piotr Łaziński, Stefan Pradelok

“…In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. To evaluate the prediction capabilities of ML, this study examines the performance of several ML algorithms in estimating the total weight and location of vehicles on a bridge using strain sensing. …”
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A Review of Computer Vision Technology for Football Videos by Fucheng Zheng, Duaa Zuhair Al-Hamid, Peter Han Joo Chong, Cheng Yang, Xue Jun Li

“…In the era of digital advancement, the integration of Deep Learning (DL) algorithms is revolutionizing performance monitoring in football. …”
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Simulation of Land Use and Land Cover Using the MOLUSCE Plugin Integrated with QGIS for the Western Himalayan Region of India by S. Kumari, S. Kumari, A. Roy

“…MOLUSCE tool is used to simulate LULC change by incorporating predictive algorithms such as Artificial Neural Networks (ANN) and Weights of Evidence (WoE). …”
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Determination of indications for the choice of the preparation method of the root canal system with rotation and reciprocation instruments by I. V. Pyatkova, L. Yu. Orekhova, T. V. Porkhun, A. V. Silin

“…Compliance with the algorithms of endodontic treatment in most cases ensures the quality of treatment. …”
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COMBINED ANALYSIS OF LINKAGE AND WHOLE EXOME SEQUENCING REVEALS CIC AS A CANDIDATE GENE FOR ISOLATED DYSTONIA by Barış Salman, Emrah Yücesan, Bedia Samancı, Başar Bilgiç, Haşmet Ayhan Hanağası, İbrahim Hakan Gürvit, Uğur Özbek, Sibel Aylin Uğur İşeri

“…An in-house pipeline compiled for WES analysis along with in-depth in silico prediction algorithms were used to assess the associated data produced in this study. …”
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Determination of Pear Cultivars (Pyrus communis L.) Based on Colour Change Levels by Using Data Mining by Dilara Gerdan, Abdullah Beyaz, Mustafa Vatandaş

“…The relationship between fruit hardness and colour change were also demonstrated. The predictions were done supervised machine learning algorithms (Decision Tree and Neural Networks with Meta-Learning Techniques; Majority Voting and Random Forest) by using KNIME Analytics software. …”
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Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning by Jian Huang, Lu Wang, Jiangfei Zhou, Tianming Dai, Weicong Zhu, Tianrui Wang, Hongde Wang, Yingze Zhang

“…By comparing the accuracy of the four machine learning models for disease prediction, the SVM model, which includes CEBPB, PTEN, ARPC1B, PIK3R1, and CDC42, was selected. …”
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Landslide Hazard Assessment Under Record-Breaking Extreme Rainfall: Integration of SBAS-InSAR and Machine Learning Models by Wenbo Zheng, Wen Fan, Yanbo Cao, Yalin Nan, Pengxu Jing

“…The proposed framework integrates cumulative extreme rainfall metrics with subtle ground deformation indicators and applies four advanced machine learning algorithms—DNN, XGBoost, RF, and LightGBM—for multidimensional hazard assessment. …”
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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

“…Hybridising the Random-Forest algorithm with Dingo optimisation and called Regulated Random Forest (RRF) to precisely identify defect clusters and then predict the welding defect growth rate (<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {{R}_{s}}$ </tex-math></inline-formula>) using the Cat-boost optimiser, which is enhanced by a beetle search mechanism called CatBAS. …”
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Application of selective ensemble learning soft sensor modeling based on GPR in the solar thermal power collection system by Yalu Sun, Kun Ding, Changhai Yang, Zhuxiu Wang

“…Finally, the set pruning strategy based on a genetic algorithm (GA) was used to select the MGPR model with high estimation performance, and the base models were fused by the Stacking algorithm to obtain the SESMGPR model. …”
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Structural and population-based evaluations of TBC1D1 p.Arg125Trp. by Tom G Richardson, Elaine C Thomas, Richard B Sessions, Debbie A Lawlor, Jeremy M Tavaré, Ian N M Day

“…We investigated these findings in the Avon Longitudinal Study of Parents and Children (ALSPAC), a large European birth cohort of mothers and offspring, and by generating a predicted model of the structure of this domain. Structural prediction involved the use of three separate algorithms; Robetta, HHpred/MODELLER and I-TASSER. …”
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