ECG‐based epileptic seizure prediction: Challenges of current data‐driven models by Sotirios Kalousios, Jens Müller, Hongliu Yang, Matthias Eberlein, Ortrud Uckermann, Gabriele Schackert, Witold H. Polanski, Georg Leonhardt

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Prediction of flood peak-discharges in the Raman Watershed, North Raman, Central Lampung by Rossi Farli, Musa Sabariah, Mera Mas, Kastamto, Susarman, Februarman

“…This research objective is to predict the flood peak-discharge in the Raman Watershed in the rainy season in December 2021. …”
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Machine Learning Models of Acute Kidney Injury Prediction in Acute Pancreatitis Patients by Cheng Qu, Lin Gao, Xian-qiang Yu, Mei Wei, Guo-quan Fang, Jianing He, Long-xiang Cao, Lu Ke, Zhi-hui Tong, Wei-qin Li

“…In the study, machine learning (ML) techniques were used to establish predictive models for AKI in AP patients during hospitalization. …”
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Mechanical Properties of Sandstones after Freeze-Thaw Cycles and Models for Their Strength Prediction by Jiaxu Jin, Junzu Ma, Bing Liang, Guosen Zhang, Shihao Yuan

“…A three-parameter strength prediction model based on σC, k0, and m is created based on the critical failure energy function. …”
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Coupling Coordination and Prediction Research of Tourism Industry Development and Ecological Environment in China by Yun Yang, Rong Wang, Junlan Tan

“…Based on the data relevant to China’s tourism industry and ecological environment from 2005 to 2018, the entropy method and the coupling coordination degree model were used to analyze the coupling degree and coupling coordination degree of the tourism industry’s development and the ecological environment, and the GM (1.1) gray model was used to predict these values in the future. The model provided predictions and illustrated the trend in the changes in the degree of coordination between the development of China’s tourism industry and the ecological environment for the next five years. …”
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Revisiting ‘revisiting supervised methods for effort‐aware cross‐project defect prediction’ by Fuyang Li, Peixin Yang, Jacky Wai Keung, Wenhua Hu, Haoyu Luo, Xiao Yu

“…Abstract Effort‐aware cross‐project defect prediction (EACPDP), which uses cross‐project software modules to build a model to rank within‐project software modules based on the defect density, has been suggested to allocate limited testing resource efficiently. …”
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Review of Prediction Models to Estimate Activity-Related Energy Expenditure in Children and Adolescents by Suzanne M. de Graauw, Janke F. de Groot, Marco van Brussel, Marjolein F. Streur, Tim Takken

“…To critically review the validity of accelerometry-based prediction models to estimate activity energy expenditure (AEE) in children and adolescents. …”
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Applying Data Analysis and Machine Learning Methods to Predict Permafrost Coast Erosion by Daria Bogatova, Stanislav Ogorodov

“…This study aims to establish a scientific and methodological basis for predicting shoreline positions using modern data analysis and machine learning techniques. …”
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Predicting oxytocin binding dynamics in receptor genetic variants through computational modeling by Preeti Dubey, Yingye Fang, K. Lionel Tukei, Shobhan Kuila, Xinming Liu, Annika Sahota, Antonina I. Frolova, Erin L. Reinl, Manasi Malik, Sarah K. England, Princess I. Imoukhuede

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Consolidation Behavior and Compression Prediction Model of Coastal Cement Soil Modified by Nanoclay by Wenjie Yu, Na Li, Mengdan Dai, Dongliang An, Biao Qian, Wei Wang, Ping Jiang

“…At curing ages of 7 days and 28 days, consolidation and SEM tests were performed on 6 groups of NCS samples with a nanoclay content between 0% and 10% and 6 groups of CCS samples with a cement content between 10 and 20%, and a compression prediction model was established based on the test results. …”
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Predicting the habitat suitability of Ilex verticillata (Aquifoliaceae) in China with field-test validations. by Yawen Yin, Zhaobin Hou, Qiuyue Sun, Bailing Zhu, Jiaqi Liu, Yiping Zou, Mingzhuo Hao

“…Field trial tests and model predictions of the suitability of I. verticillata were consistent, indicating that our model predictions are biologically meaningful and economically valuable. …”
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Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models by Filipe Augusto Felix de Queiroz, Igor Barbosa Negreiros, Giovana de Souza, Débora Cordeiro de Sousa, Sílvio Fernando Alves Xavier Júnior

“…We compare different statistical modeling and Machine Learning techniques, identifying the ones with the greatest accuracy in predicting sentiments. As a result, the assessment supports most of the sentences presented with negative connotations. …”
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MODEL PREDICTIVE CONTROL FOR PHOTOVOLTAIC STATION MAXIMUM POWER POINT TRACKING SYSTEM by I. Elzein, Yu. N. Petrenko

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Risk Factors and Predictive Model for Disseminated Intravascular Coagulation in Patients with Multiple Myeloma by Rong Bao MM, Mengtong Fan MM, Min Hu MM, Ling Li BD,   Hasichaolu BD

“…We also sought to develop a predictive formula for assessing DIC risk. Methods A retrospective analysis was conducted on MM patients. …”
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Comparison of Per Cent Predicted and Percentile Values for Pulmonary Function Test Interpretation by Smita Pakhale, Zoheir Bshouty, Theodore K Marras

“…BACKGROUND: Pulmonary function tests (PFTs) are commonly interpreted as a fraction of predicted normal values, with an abnormal test often defined as less than 80% or greater than 120% of the predicted value. …”
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A telomere-related signature for predicting prognosis and assessing immune microenvironment in osteosarcoma by Shihao Li, Lina Zhang, Haiyang Zhang

“…In addition, the telomere-related signature demonstrated predictive value for the immune microenvironment and drug sensitivity in osteosarcoma. …”
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Predicting the Risk of Fundus Lesions in Systemic Lupus Erythematosus: A Nomogram Model by Huan Xie, Fangfang Sun, Huimin Yang, Jin Li

“…This study aimed to use laboratory and clinical data of systemic lupus erythematosus (SLE) patients to construct prediction models for fundus complications in SLE. Methods. …”
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Corrigendum to “Prediction of Pollutant Emissions from Bluff-Body Stabilised Nonpremixed Flames” by Nelu Munteanu, Shokri Amzin

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Using Molecular Markers to Help Predict Who Will Fail after Radical Prostatectomy by Gregory P. Swanson, David Quinn

“…There is great interest in being able to accurately predict who is at risk of failure to avoid treating those who may not benefit. …”
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A Modeling Strategy for Predicting the Response of Steel Plate-Concrete Composite Walls by Mohammad Sadegh Barkhordari

“…In this study, a new semi-macro modified fixed strut angle finite element model is proposed to predict the nonlinear response of SCC walls using OpenSees. …”
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