Implementing Symptom-Based Predictive Models for Early Diagnosis of Pediatric Respiratory Viral Infections by Antoni Soriano-Arandes, Cristina Andrés, Aida Perramon-Malavez, Anna Creus-Costa, Anna Gatell, Ramona Martín-Martín, Elisabet Solà-Segura, Maria Teresa Riera-Bosch, Eduard Fernández, Mireia Biosca, Ramon Capdevila, Almudena Sánchez, Isabel Soler, Maria Chiné, Lidia Sanz, Gabriela Quezada, Sandra Pérez, Dolors Canadell, Olga Salvadó, Marisa Ridao, Imma Sau, Ma Àngels Rifà, Esperança Macià, Sílvia Burgaya-Subirana, Mònica Vila, Jorgina Vila, Asunción Mejías, Andrés Antón, Pere Soler-Palacin, Clara Prats

“…This study assessed the effectiveness of machine learning-based models in estimating infection probabilities for these common pediatric respiratory viruses, using symptom data. (2) Methods: Data were collected from 868 children with ARI symptoms evaluated across 14 primary care centers, members of COPEDICAT (Coronavirus Pediatria Catalunya), from October 2021 to October 2023. …”
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Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors by Shaofen Huang, Man Luo, Guitong Ye, Zhenlan Yang, Lingling Liao, Nina Wu, Yingting Zhu, Xing Liu, Yehong Zhuo, Hui Xiao

“…We aimed to develop a model for predicting OHT progression to early glaucoma and to identify key predictors. …”
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Construct and Predictive Validity of the Kansas City Cardiomyopathy Questionnaire in Adult Congenital Heart Disease by Ryan D. Byrne, MD, Ajith P. Nair, MD, Stephen J. Dolgner, MD, Swati Choudhry, MD, Edward J. Hickey, MD, Alexis C. Wood, PhD, Savitri Fedson, MD, Biykem Bozkurt, MD, PhD, Christopher R. Broda, MD

“…Objectives: This study evaluates construct and predictive validity of the KCCQ in ambulatory ACHD patients. …”
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Metabolome Profiling and Predictive Modeling of Dark Green Leaf Trait in Bunching Onion Varieties by Tetsuya Nakajima, Mari Kobayashi, Masato Fuji, Kouei Fujii, Mostafa Abdelrahman, Yasumasa Matsuoka, Jun’ichi Mano, Muneo Sato, Masami Yokota Hirai, Naoki Yamauchi, Masayoshi Shigyo

“…This study aimed to elucidate the mechanisms regulating the dark green trait and develop a predictive model for accurately assessing pigment composition. …”
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BLASTING BEYOND THE OBVIOUS: IDENTIFICATION OF OVERLOOKED PREDICTIVE FACTORS FOR LEUKEMIC CONVERSION IN MYELODYSPLASTIC NEOPLASMS by PRC Passos, RDB Dias, SCC Carneiro, IB Nogueira, JMGF Lima, RC Venâncio, ACG Lavor, JVG Gama, RF Pinheiro, SMM Magalhães

“…Methods: We conducted a retrospective cohort at a single reference center, involving patients diagnosed with MDS between 2004 and 2024. …”
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Transcriptional landscape and predictive potential of long noncoding RNAs in peritoneal recurrence of gastric cancer by Xiao-Xia Cai, Guo-Ming Chen, Zi-Qi Zheng, Yi-Xin Yin, Shuang Wang, Li Qiao, Xiao-Jiang Chen, Bai-Wei Zhao, Jin-Ling Duan, Cheng-Cai Liang, Ruo-Peng Zhang, Cheng-Zhi Wei, Fei-Yang Zhang, Bo-Wen Huang, Ze-Xian Liu, Zhi-Wei Zhou, Dan Xie, Mu-Yan Cai, Shu-Qiang Yuan, Yuan-Fang Li, Run-Cong Nie

“…However, research comprehensively exploring tissue-derived lncRNAs for predicting peritoneal recurrence in patients with GC remains limited. …”
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Modeling and Predicting Time Series with Non-stationarity and Volatility by FENG Qiang, ZHAO Jianguang, YANG Rong, NIU Baoning

“…By decomposing the original sequence into a set of components, this method ensures the integrity of trend and periodic characteristics while increasing the proportion of stationary components in the component set, providing more stable data for the prediction model. …”
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Mining Linguistic Associations for Emergent Flood Prediction Adjustment by Michal Burda, Pavel Rusnok, Martin Štěpnička

“…An application of fuzzy GUHA method in flood peak prediction is presented. Measured water flow rate data from a system for flood predictions were used in order to mine fuzzy association rules expressed in natural language. …”
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Adversarial defense for battery state-of-health prediction models by Masoumeh Mohammadi, Insoo Sohn

“…We analyze the impact of adversarial data poisoning attacks on SOH prediction models, specifically employing the fast gradient sign method (FGSM) and iterative fast gradient sign method (IFGSM). …”
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An Improved KNN-Based Slope Stability Prediction Model by Shuai Huang, Mingming Huang, Yuejun Lyu

“…Moreover, a comparison between our proposed prediction model and the finite element method, which is the classical theoretical method of slope stability, was made, which will provide an important approach to predicting the slope stability for slope engineering. …”
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Advances in Neural Network assisted Tool Pressure Prediction by Göltl Florian, Harst Felix, Birkert Arndt, Stache Nicolaj C.

“…In this process, the CNN output is scaled to absolute values using the known total integral force, allowing the post-processing method to extrapolate the predicted pressure distribution effectively, even in untrained regions.…”
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How Can We Predict Success in Poor Responders? by Alina Elena BORDEA, Elvira BRATILA, Diana MIHAI, Marina ANTONOVICI, Claudia MEHEDINTU, Andreea CARP-VELISCU

“…Objectives: The aim of this study was to evaluate how can we predict success in poor responder patients in terms of pregnancy rate and live birth rate. …”
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Naive Bayes Analysis for Nutritional Fulfillment Prediction in Children by Satrio Agung Wicaksono, Satrio Hadi Wijoyo, Fatmawati Fatmawati, Tri Afirianto, Diva Kurnianingtyas, Mochammad Chandra Saputra

“…Key performance metrics were evaluated to validate the model's predictive capabilities, including accuracy, precision, recall, and F1-score. …”
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Cross-Project Defect Prediction: A Literature Review by Sourabh Pal, Alberto Sillitti

“…Due to the lack of availability of software engineering data from the same project, the researchers proposed cross-project defect prediction (CPDP) models where the data collected from one or more projects are used to predict faults in other project. …”
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The role of CT in prognosis prediction in COVID-19 patients by Tonje Gravdal, Kine Storås, Albertina Rusandu, Ragna Stalsberg

“… Introduction: The aim of the present study was to summarize and evaluate previously published scientific studies examining whether computed tomography (CT) of the thorax can predict the COVID-19 prognosis. …”
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Probabilistic prediction of Load–Displacement curves of corroded strands by Seungjun Lee, Jaebeom Lee, Chi-Ho Jeon, Young-Joo Lee

“…This study proposes a probabilistic method for predicting the non-linear mechanical behavior of corroded steel strands. …”
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A Computational Framework to Predict the Soccer Ball Trajectory by Pierluigi Maponi, Riccardo Piombin

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Application of Machine Learning Models for Baseball Outcome Prediction by Tzu-Chien Lo, Chen-Yin Lee, Chien-Lin Chen, Tsung-Yu Hsieh, Che-Hsiu Chen, Yen-Kuang Lin

“…Data science has become an essential component in professional sports, particularly for predicting team performance and outcomes. This study aims to develop and evaluate machine learning models that accurately predict game outcomes in the Chinese Professional Baseball League (CPBL). …”
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COMPARATIVE MACHINE LEARNING ALGORITHM FOR CARDIOVASCULAR DISEASE PREDICTION by Ashish Mishra, Jyoti Mishra, Victor Hugo, Aloísio Vieira Lira Neto

“…The preliminary examination and evaluation predicted heart problems. The dataset has 303 samples with 14 features. …”
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Synchrophasor-Based Out-of-Step Prediction in Large Grids by Zainab Alnassar, S. T. Nagarajan

“…The prediction speed of proposed method is found to be between 5% and 70% of time to OOS, after disturbance clearance. …”
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