Nonconcordance between Clinical and Head CT Findings: The Specter of Overdiagnosis by Kelli N. O'Laughlin, Jerome R. Hoffman, Steven Go, Gelareh Z. Gabayan, Erum Iqbal, Guy Merchant, Roberto A. Lopez-Freeman, Michael I. Zucker, William R. Mower

“…It is unclear whether history and physical examination findings can predict abnormalities on head computed tomography (CT) believed to indicate increased risk of lumbar-puncture- (LP-) induced brain herniation. …”
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Integrating principal component analysis, fuzzy inference systems, and advanced neural networks for enhanced estuarine water quality assessment by Richard O. Usang, Bamidele I. Olu-Owolabi, Kayode O. Adebowale

“…New hydrological insights for the region: The hybrid LSTM-CNN model demonstrated superior predictive performance, achieving RMSE values lower than 10 % and R² values exceeding 0.90 across various predictive tasks, indicating high accuracy in forecasting water quality parameters. …”
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Performance of artificial neural networks and traditional methods in determining selected growth parameters of Alburnus sellal Heckel, 1843 by Ozcan Ebru Ifakat

“…They have been found to be a useful predictive tool. The developed models can be used to predict future sustainable fish management.…”
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Symmetry-Aware 6D Object Pose Estimation via Multitask Learning by Hongjia Zhang, Junwen Huang, Xin Xu, Qiang Fang, Yifei Shi

“…Moreover, we devise an optimization function to refine the predicted 6D object pose by considering the predicted symmetry. …”
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Study on the correlation of toughness with chemical composition and tensile test results in microalloyed API pipeline steels by Pouraliakbar H., Khalaj G., Jandaghi M.R., Khalaj M.J.

“…Additionally, the model was also employed to predict the toughness of 26 newly tested steels. The predicted values were in very good agreement with the measured ones indicating that the developed model was very accurate and had the great ability for predicting the toughness of pipeline steels.…”
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Evaluation of the Impacts of Assimilating the TAMDAR Data on 12/4 km Grid WRF-Based RTFDDA Simulations over the CONUS by Yongxin Zhang, Yubao Liu, Thomas Nipen

“…Assimilating the TAMDAR data improves temperature predictions at middle to high levels and wind speed predictions at all levels especially for the 12 km domain. …”
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Humans rationally balance detailed and temporally abstract world models by Ari E. Kahn, Nathaniel D. Daw

“…The current study extends these ideas from simple habits into usage of more sophisticated approximate predictive models, and demonstrates that individuals dynamically adapt these in response to the predictability of their environment.…”
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PM10 AIR POLLUTION IN MASHAD CITY USING ARTIFICIAL NEURAL NETWORK AND MAKOV CHAIN MODEL

“…The results indicated the optimal performance of these methods in predicting of the amount of pollutants and also the probability of occurrence of hours with different quality of contamination. …”
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Prevalence and predictors of severe Crohn’s disease at a tertiary hospital in South Africa by C Gounden, V Naidoo, Y Moodley

“… Background Predicting severe Crohn's disease (SCD) can assist in planning risk reduction therapy for SCD, thereby improving disease outcomes. …”
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A Novel Nomogram for Early Identification of CFS-Like Symptoms in University Students with Infectious Mononucleosis by Deping Sun, Yanan Liang, Fuwei Yang, Lan Liu, Yuqin Yan

“…This study aims to develop and evaluate a nomogram for predicting the risk of chronic fatigue syndrome (CFS)-like symptoms in university students diagnosed with infectious mononucleosis (IM), using clinical characteristics and laboratory findings as predictive variables. …”
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Structural modeling of NAD+ binding modes to PARP-1 by N. V. Ivanisenko, D. A. Zhechev, V. A. Ivanisenko

“…We designed two NAD+ derivatives, which can be used for validation of predicted NAD+ binding models.…”
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Diagnostic Value of the 13C Methacetin Breath Test in Various Stages of Chronic Liver Disease by Hamizah Razlan, Nurhayaty Muhamad Marzuki, Mei-Ling Sharon Tai, Azhar-Shah Shamsul, Tze-Zen Ong, Sanjiv Mahadeva

“…Diagnostic accuracy of the breath test was determined by sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve analysis. …”
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Joint embedding–classifier learning for interpretable collaborative filtering by Clémence Réda, Jill-Jênn Vie, Olaf Wolkenhauer

“…An interpretable classifier quantifies the importance of each input feature for the predicted item-user association in a non-ambiguous fashion. …”
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Axion dark matter, proton decay and unification by Pavel Fileviez Pérez, Clara Murgui, Alexis D. Plascencia

“…Abstract We discuss the possibility to predict the QCD axion mass in the context of grand unified theories. …”
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Performance Evaluation of an Air-Conditioning Compressor Part I: Measurement and Design Modeling by Thomas W. Bein, Yu-Tai Lee

“…Part II of this paper provides predictions of flow details in the areas of the compressor where there were differences between the measured and predicted performance.…”
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Dual-Channel Reasoning Model for Complex Question Answering by Xing Cao, Yun Liu, Bo Hu, Yu Zhang

“…Most existing methods predict the final answer and evidence sentences in sequence or simultaneously, which inhibits the ability of models to predict the path of reasoning. …”
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Evaluation of Temper Embrittlement of 30Cr2MoV Rotor Steels Using Electrochemical Impedance Spectroscopy Technique by Zhang Shenghan, Lv Yaling, Tan Yu

“…The results show that there was a linear relationship of interfacial impedance of the specimens and their FATT50 values. The predictive error based on the experiment study is within the range of ±15°C, indicating the predicting model is precise, effective, and reasonable.…”
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An Assessment of the Utility of a Bayesian Framework to Improve Response Propensity Models in Longitudinal Data by Eliud Kibuchi, Gabriele B Durrant, Olga Maslovskaya, Patrick Sturgis

“…One application is to predict sample members who are likely to be survey nonrespondents. …”
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An Augmented Classical Least Squares Method for Quantitative Raman Spectral Analysis against Component Information Loss by Yan Zhou, Hui Cao

“…Results indicated that the proposed method is effective at increasing the robust predictive power of traditional CLS model against component information loss and its predictive power is comparable to that of PLS or PCR.…”
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Relationships among COVID-19 causal factors perceived by children, basic psychological needs and social anxiety by Higinio González-García, Leandro Álvarez-Kurogi, Joel Prieto Andreu, Javier Tierno Cordón, Rosario Castro López, Jesús Salas Sánchez

“…Objective To examine whether COVID-19 causal factors perceived by children predicted basic psychological needs and social anxiety, and if basic psychological needs predicted social anxiety. …”
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