Optimizing axial length estimation for intraocular lens power calculation in phacovitrectomy for macula-off retinal detachment by Sukhum Silpa-archa, Chitchanok Samanwongthai, Variya Nganthavee, Korawin Charoensuk

“…The primary outcome was the mean absolute prediction error (MAE) between postoperative AL and preoperative estimates generated by five methods, including two novel algorithms. …”
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The Analysis of Communication Strategy of Disabled Sports Information Based on Deep Learning and the Internet of Things by Wanglong Wang, Qingwen Liu, Chuan Shu

“…The ever-growing landscape of Internet of Things (IoT) technology and the evolution of deep learning algorithms have ushered in transformative changes in the communication strategy for disseminating information on disabled sports. …”
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Combination of Feature Selection and Learning Methods for IoT Data Fusion by V. Sattari-Naeini, Zahra Parizi-Nejad

“…All the schemes consist of four stages, including preprocessingthe data set based on curve fitting, reducing the data dimension and identifying the most effective featuresets according to data correlation, training classification algorithms, and finally predicting new databased on classification algorithms. …”
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Design and development of full self-service smart shopping system for unmanned supermarket by Xiao Liang, Yu Qi, Shuo Xi, Guanglei Meng, Zhujun Wang

“…Additionally, integrating a distributed DIMP (Discriminative Model Prediction) visual-tracking algorithm and infrared range sensors ensures that the smart shopping cart always follows the customer at a safe distance. …”
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Method for reconstructing safety and arming motion process by integrating Kalman filter and KCF by Yinhuan Zhang, Qinkun Xiao, Xing Liu, Yongquan Wei, Jingyun Xue

“…On the OTB100 dataset, it attains 92.50% accuracy and 68.10% success rate, outperforming other related filtering algorithms. These results highlight significant improvements in tracking accuracy and success rate, demonstrating the algorithm’s robustness in handling challenging tracking scenarios. …”
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MLRec: A Machine Learning-Based Recommendation System for High School Students Context of Bangladesh by Momotaz Begum, Mehedi Hasan Shuvo, Jia Uddin

“…After that, we applied 15 ML algorithms for training and testing. Then, we compared the algorithms using criteria such as accuracy, Mean Squared Error (MSE), Root Mean Squared Error (RMSE), coefficient of determination (R²), Explained Variance (EV), and Tweedie Deviance Score (D²). …”
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AMMap tool for additive manufacturing design, alloy discovery, and path planning by Alexander M Richter, Adam M Krajewski, Zhening Yang, Allison M Beese, Zi-Kui Liu

“…Equilibrium thermodynamic calculations and solidification simulations, such as Scheil–Gulliver, can be used to predict feasible compositions or compositional paths, acting as constraints before empirical or machine learning models are applied to predict properties of interest. …”
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THE APPROVAL OF COMPLEX TREATMENT EFFECTIVENESS OF GENERALIZED PERIODONTITIS FOR THE PATIENTS AFTER TRANSMITTED CORONAVIRUS DISEASE AND REMAIN ON REHABILITATION by T.I. Matviykiv, M.M. Rozhko

“…Examination of areas compromised by generalized periodontitis and abutment teeth based on the obtained periotestometric data of tooth mobility, indicates a significant reduction in inflammation and strengthening of the ligaments and is a highly informative diagnostic method. …”
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Outdoor Environment Design Optimization of an Office Building Based on Indoor Thermal Conditions and Building Energy Performance by Yaolin Lin, Tao Huang, Wei Yang, Melissa Chan, Chun-Qing Li, Mingqi Dai, Pengju Chen

“…Thirdly, two machine learning prediction algorithms were used to develop discomfort degree hours and energy consumption models, and the artificial neural network models were found to have better prediction performance with R-squares greater than 0.99. …”
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Modelling the Isotope composition of groundwater using hydrochemical properties in eastern Saudi Arabia: Implementation of innovative data intelligence techniques by Mohammed Benaafi, Waleed M. Hamanah, Ebrahim Al-Wajih

“…New hydrological insight for the region: Eight AI algorithms (KNN, SVR, RF, ET, Bag, AdaBt, GRB, and CAT) and stacking ensemble models were developed to predict the δ¹ ⁸O and δ²H isotopes of the groundwater using a dataset of physicochemical parameters, ions and elements, and isotopes from 47 wells. …”
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Enhancing blockchain transaction classification with ensemble learning approaches by Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Rourab Paul, Ajit Kumar Nayak, Subrata Chowdhury, Ramya Govindaraj, J Shreyas

“…Various ML classification algorithms are applied to the selected features from two ensemble feature selection algorithms as the base learners to make initial predictions. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…The results demonstrate ANFIS as the superior model, consistently outperforming other algorithms across all metrics. By synergizing fuzzy logic’s capacity to model uncertainty with neural networks’ adaptive learning, ANFIS effectively captures non-linear relationships and variations in employee performance, enabling precise capability predictions in dynamic environments. …”
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Estimating Energy Consumption During Soil Cultivation Using Geophysical Scanning and Machine Learning Methods by Jasper Tembeck Mbah, Katarzyna Pentoś, Krzysztof S. Pieczarka, Tomasz Wojciechowski

“…These data, along with soil texture, served as inputs for predicting fuel consumption and field productivity. …”
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Duty of care, data science, and gambling harm: A scoping review of risk assessment models by Virve Marionneau, Kim Ristolainen, Tomi Roukka

“…Online operators often employ risk detection algorithms to accomplish this task. This scoping review focuses on how such data science applications can perform from a duty of care perspective. …”
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Carbonate Seismic Facies Analysis in Reservoir Characterization: A Machine Learning Approach with Integration of Reservoir Mineralogy and Porosity by Papa Owusu, Abdelmoneam Raef, Essam Sharaf

“…To this end, this study utilizes an unsupervised comparative hierarchical and K-means ML classification of the whole 3D seismic data spectrum and a suite of spectral bands to overcome the cluster “facies” number uncertainty in ML data partition algorithms. This comparative ML, which was leveraged with seismic resolution data preconditioning, predicted geologically plausible seismic facies, i.e., seismic facies with spatial continuity, consistent morphology across seismic bands, and two ML algorithms. …”
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Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li, Hui Chen, Hua Duan

“…The study evaluated two image-deep-learning algorithms’ effectiveness in predicting pregnancy within one year, using AUCs and decision curve analysis. …”
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Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads by Keyong Hu, Qingqing Yang, Lei Lu, Yu Zhang, Shuifa Sun, Ben Wang

“…In modeling uncertainties, this article utilizes historical data on PV, WT, and loads, combined with the adjustability of decision variables, to generate a large set of initial scenarios through the Monte Carlo (MC) sampling algorithm. These scenarios are subsequently reduced using a combination of the K-means clustering algorithm and the Simultaneous Backward Reduction (SBR) technique to obtain representative scenarios. …”
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PATH CONTROL AIRCRAFT OF TRAJECTORY UNDER THE INFLUENCE OF DISTURBANCES ON AN DUAL CHANNEL by S. A. Kabanov, F. V. Mitin

“…The problem is solved using the algorithm with the predictive model.…”
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An Explainable Fuzzy Framework for Assessing Preeclampsia Classification by Matías Salinas, Daira Velandia, Leondry Mayeta-Revilla, Ayleen Bertini, Marvin Querales, Fabian Pardo, Rodrigo Salas

“…There is a critical need for predictive systems that not only perform accurately but also provide interpretable insights for clinical decision-making. …”
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Digital Twin and TD3-Enabled Optimization of xEV Energy Management in Vehicle-to-Grid Networks by Irum Saba, Abdulraheem H. Alobaidi, Sultan Alghamdi, Muhammad Tariq

“…However, traditional ESS management approaches struggle with real-time state estimation, energy optimization, and predictive maintenance, leading to inefficiencies in battery utilization and sustainability. …”
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