Assessing accuracy of BiliPredics algorithm in predicting individual bilirubin progression in neonates—results from a prospective multi-center study by Britta Steffens, Britta Steffens, Gilbert Koch, Gilbert Koch, Corinna Engel, Axel R. Franz, Marc Pfister, Marc Pfister, Marc Pfister, Sven Wellmann, Sven Wellmann

“…The recently developed BiliPredics algorithm, integrated in the first CE-approved bilirubin prediction tool, predicts individual bilirubin progression for up to 60 h into the future. …”
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A prototype-based rockburst types and risk prediction algorithm considering intra-class variance and inter-class distance of microseismic data by Xiufeng Zhang, Guoying Li, Yang Chen, Hao Wang, Haikuan Zhang, Haitao Li, Weisheng Du, Xiao Li, Xuewei Xu, Yuze He

“…Therefore, based on the quantitative study of the relationship between the performance of a deep learning prediction algorithm and a rockburst prediction vector, a rockburst risk and type prediction algorithm based on a convolutional neural network (CNN)-gated recurrent unit (GRU) model with prototype-based prediction is proposed. …”
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A voice-based algorithm can predict type 2 diabetes status in USA adults: Findings from the Colive Voice study. by Abir Elbéji, Mégane Pizzimenti, Gloria Aguayo, Aurélie Fischer, Hanin Ayadi, Franck Mauvais-Jarvis, Jean-Pierre Riveline, Vladimir Despotovic, Guy Fagherazzi

“…This study investigates the potential of using a voice-based algorithm to predict T2D status in adults, as the first step towards developing a non-invasive and scalable screening method. …”
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A Prediction Model of Stable Warfarin Doses in Patients After Mechanical Heart Valve Replacement Based on a Machine Learning Algorithm by Bowen Guo, Cong Chen, Junhang Jia, Jubing Zheng, Yue Song, Taoshuai Liu, Kui Zhang, Yang Li, Ran Dong

“…The variables were selected using analysis of covariance (ANCOVA). Algorithms for predicting the stable warfarin dose were constructed using a traditional linear model, general linear model (GLM), and 10 ML algorithms. …”
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A Multi-objective Cluster-based Biased Random-Key Genetic Algorithm with Online Parameter Control Applied to Protein Structure Prediction by Felipe Marchi, Rafael Stubs Parpinelli

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The utility of liver function tests for mortality prediction within one year in primary care using the algorithm for liver function investigations (ALFI). by David J McLernon, John F Dillon, Frank M Sullivan, Paul Roderick, William M Rosenberg, Stephen D Ryder, Peter T Donnan

“…As an example of performance, for a 10% predicted probability cut-off, sensitivity = 52.8%, specificity = 94.0%, PPV = 21.0%, NPV = 98.5%. …”
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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. …”
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Data-Selective Learning Algorithm Using Resonance Parameters Based on Stacked Data Augmentation for Wideband Impedance Prediction of Printed Spiral Coils by Joojoong Kim, Eakhwan Song

Subjects: “…data selective learning algorithm…”
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Radial Basis Function Neural Network Based on an Improved Exponential Decreasing Inertia Weight-Particle Swarm Optimization Algorithm for AQI Prediction by Jinna Lu, Hongping Hu, Yanping Bai

“…Based on the inertia weight decreasing strategy, we propose a new Exponential Decreasing Inertia Weight (EDIW) to improve the PSO algorithm. We use the modified EDIW-PSO algorithm to determine the centers, widths, and connection weights of RBF neural network. …”
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Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images by Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan, Achraf Ben Miled, Da’ad Albalawneh, Abdulwhab Alkharashi, Samah Al Zanin, Radwa Marzouk

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ICESat-2 Satellite LiDAR Bathymetry Extraction Algorithm Based on Cubic Function Fitting Prediction Interval Along Track Segments by Junyuan Chen, Yi Ma, Yang Jiang, Kun Jia, Aijun Cui, Xuechun Zhang, Shaohui Li, Jingyu Zhang

“…Based on the continuously changing characteristics of the seafloor topography, this article proposes an ICESat-2 bathymetry extraction algorithm based on cubic function fitting prediction interval along track segments. …”
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Corrigendum: Spatial-temporal evolution characteristics and driving factors of carbon emission prediction in China-research on ARIMA-BP neural network algorithm by Sanglin Zhao, Zhetong Li, Hao Deng, Xing You, Jiaang Tong, Bingkun Yuan, Zihao Zeng

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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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A novel hybrid machine learning approach for δ13C spatial prediction in polish hard-water lakes by Himan Shahabi, Ataollah Shirzadi, Alicja Ustrzycka, Natalia Piotrowska, Janusz Filipiak, Marzieh Hajizadeh Tahan

Subjects: “…Carbon-13 predicting…”
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Assessing Crash Reduction at Stop-Controlled Intersections: A Before-After Study of LED-Backlit Signs Using Crash and Conflict Data by Maziyar Layegh, Ciprian Alecsandru, Matin Giahi Foomani

“…The results showed significant conflict reductions at intersections with LED-backlit signs (BLSs), including 65.5% at night and 46.8% in daylight. …”
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Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

Subjects: “…Student Performance Prediction…”
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Application of Battery Life Prediction Technology in EMUs by DAI Yi, YU Tianjian, CHENG Shu, WU Xun, LIU Jiawen

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An interpretable predictive model for bank customers’ income using the eXtreme Gradient Boosting algorithm and the SHAP method: a case study of an Anonymous Chilean Bank by Patricio Salas, Patricio Sáez, Vicente Marchant

“…Feature reduction is accomplished through the implementation of Boruta and BorutaSHAP, ensuring that no predictive power is lost throughout the process. …”
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Alzheimer’s Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models by Sameer Abbas, Mustafa Yeniad, Javad Rahebi

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Predicting Movie Production Years through Facial Recognition of Actors with Machine Learning by Asraa Muayed Abdalah, Noor Redha Alkazaz

Subjects: “…Artificial Intelligence, Machine Learning Algorithms, Face Recognition, Age Prediction, Naive Bayes (NB), Decision Tree (DT), Support Vector Machine (SVM), and Artificial Neural Network (ANN)…”
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