Development and evaluation of machine learning models for individualized prediction of myopia control efficacy treated with overnight orthokeratology by Lan Zhang, Mingjun Gao, Yiru Wang, Siqi Zhang, Huailin Zhu, Qi Zhao

“…The prediction performance was evaluated according to the accuracy and AUC of the training set and the test set. …”
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Comparative Performance Analysis of Optimization Algorithms in Artificial Neural Networks for Stock Price Prediction by Ekaprana Wijaya, Moch. Arief Soeleman, Pulung Nurtantio Andono

“…This study aims to enhance price prediction accuracy using Artificial Neural Networks (ANN) by comparing three optimization methods: Stochastic Gradient Descent (SGD), Adam, and RMSprop. …”
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Evaluation of fractured carbonate reservoir and prediction of favorable areas in the eastern area of Amu Darya Right Bank by Yang Li, Xiaodong Cheng, Leyuan Fan, Liguo Sun, Jiapeng Wu, Jiao Wei

“…Given the strong correlation between fracture development and productivity, analyzing fractures is crucial. Comprehensive evaluation and prediction methods for fractured reservoirs are essential for advancing the oil and gas industry. …”
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Contrasting aerial moose population estimation methods and evaluating sightability in west‐central Alberta, Canada by Wibke Peters, Mark Hebblewhite, Kirby G. Smith, Shevenell M. Webb, Nathan Webb, Mike Russell, Curtis Stambaugh, Robert B. Anderson

“…In this case study, we evaluated the application of distance sampling as an alternative to block‐surveys in Alberta, Canada. …”
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Evaluation of drug release from topical dosage forms and permeability prediction through the skin barrier (review) by N. B. Melnikova, I. A. Sheferov, A. A. Emasheva, A. A. Sheferova, D. A. Panteleev, A. I. Slivkin

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A Novel Deep Learner for Human Behavior Prediction Over Public Video Surveillance by Bayan Alabdullah, Bisma Batool Fatima, Haifa F. Alhasson, Mohammed Alshehri, Yahya AlQahtani, Nouf Albhassabi, Hui Liu

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Comprehensive evaluation of the MeltPro MTB/PZA assay for prediction of pyrazinamide resistance in multidrug-resistant tuberculosis by Guiqing He, Chunxia Tu, Yelei Zhu, Qingyong Zheng, Qiulong Zhou, Wenzhen Zhou, Ouyang Huang, Bin Chen, Zhengwei Liu, Ye Xu, Xiangao Jiang

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Uncertainty and Prediction Intervals of New Machine Learning Approach for Non-Destructive Evaluation of Concrete Compressive Strength by Seyed Alireza Alavi, Martin Noel

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Development of a deep learning-based model for predicting of dominant seepage channels in oil reservoirs by Chen Liu, Zenghua Zhang, Wensheng Zhou, Chengyu Luo, Lei Jiang

“…It employs an evaluation method for the development of dominant seepage channels and a label matrix for seepage channels. …”
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A Data-Driven Approach for Urban Heat Island Predictions: Rethinking the Evaluation Metrics and Data Preprocessing by Berk Kıvılcım, Patrick Erik Bradley

“…The trained models with Random Forest and XGBoost methods which are capable of predicting the spatial distribution of air temperature by using building volume information are compared. …”
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A Review on New Frontiers in Drug-Drug Interaction Predictions and Safety Evaluations with In Vitro Cellular Models by Lara Marques, Nuno Vale

“…This review provides a comprehensive overview of both conventional and novel strategies for DDI predictions, highlighting their strengths and limitations. …”
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Retrospective evaluation of a novel ultrasound-based imaging analysis software for predicting radiofrequency ablation areas. by Masaya Sato, Ryosuke Tateishi, Yogev Zohar, Jiro Sato, Takeyuki Watadani, Makoto Moriyama, Taijiro Wake, Ryo Nakagomi, Mizuki Nishibatake Kinoshita, Takuma Nakatsuka, Tatsuya Minami, Koji Uchino, Kenichiro Enooku, Hayato Nakagawa, Yoshinari Asaoka, Ryo Yamada, Nitzan Even, Inbal Amitai, Yossi Abu, Mitsuhiro Fujishiro, Kazuhiko Koike

“…Its predictive accuracy was assessed by comparing the ablation zones it predicted with those annotated by radiologists using contrast-enhanced computed tomography (CECT) 24 hours post-treatment, considered the gold standard. …”
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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

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Design and Evaluation of Noise Simulation Algorithm Using MATLAB Ray Tracing Engine for Noise Assessment and Prediction by Precin Kalisalvan, Mohd Sayuti Ab Karim, Siti Nurmaya Musa

“…To address this, accurate risk assessment is crucial. The current noise evaluation methods are complex and time-consuming, relying on manual calculations and field measurements. …”
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506 Evaluating prediction models for conversion of clinically isolated syndrome to multiple sclerosis: A systematic review by Mei-An Nolan, Danielle Howard, James Beck

“…Studies will be evaluated for overall risk of bias using PROBAST (Prediction model Risk Of Bias Assessment Tool). …”
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Large language models' knowledge of children's memory and suggestibility: Evaluating model predictions of prior experimental results by Pekka Santtila, Yongjie Sun, Kristjan Kask, Liisa Järvilehto, Jiaxing Xiu

“…Methods: The models were assessed on their prediction accuracy, with overall and model-specific performance analyzed using chi-square tests. …”
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Ultrasound evaluation of gallbladder wall thickness for predicting severe dengue: a systematic review and meta-analysis by Amirhossein Shahsavand Davoudi, Hamid Harandi, Reza Samiee, Shayan Forghani, Keyhan Mohammadi, Maryam Shafaati

“…Aims This systematic review and meta-analysis evaluated the predictive value of GBWT in identifying patients at risk for severe dengue. …”
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Device-Based Cellular Throughput Prediction for Video Streaming: Lessons From a Real-World Evaluation by Darijo Raca, Ahmed H. Zahran, Cormac J. Sreenan, Rakesh K. Sinha, Emir Halepovic, Vijay Gopalakrishnan

“…The focus of this paper is an empirical investigation of machine learning-based throughput prediction that runs in real-time on a smartphone, and its evaluation with video streaming in a range of real-world cellular network settings. …”
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Evaluation of Feature Selection and Regression Models to Predict Biomass of Sweet Basil by Using Drone and Satellite Imagery by Luana Centorame, Nicolò La Porta, Michela Papandrea, Adriano Mancini, Ester Foppa Pedretti

“…Feature selection was performed using three different methods (F-score, Recursive Feature Elimination, and model-based selection), and the most informative features were then processed through Principal Component Analysis. …”
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