SevPredict: Exploring the Potential of Large Language Models in Software Maintenance by Muhammad Ali Arshad, Adnan Riaz, Rubia Fatima, Affan Yasin

“…The comparative analysis between the proposed approach and state-of-the-art approaches suggests that the proposed approach outperforms the state-of-the-art approaches in terms of performance evaluation metrics. SevPredict shows improvements over the best-performing state-of-the-art approach (BERT-SBR) with 1.72% higher accuracy, 2.18% higher precision, and 4.94% higher MCC. …”
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Development and validation of an interpretable risk prediction model for the early classification of thalassemia by Jin-Xin Lai, Jia-Wei Tang, Shan-Shan Gong, Ming-Xiong Qin, Yu-Lu Zhang, Quan-Fa Liang, Li-Yan Li, Zhen Cai, Liang Wang

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Machine learning for predicting resistance spot weld quality in automotive manufacturing by Nuttapong Chuenmee, Nattachai Phothi, Kontorn Chamniprasart, Sorada Khaengkarn, Jiraphon Srisertpol

“…Despite its advantages, accurately evaluating RSW remains challenging, resulting in additional costs and production steps. …”
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Lysosome-derived biomarkers for predicting survival outcome in acute myeloid leukemia by Gongchang Li, Yangyang Miao, Fang Yuan, Weiran Zhang, Yali Wu, Liqiang Zhu

“…In summary, a six-LRGs-related signature was developed to predict the prognosis of AML patients, and more research is necessary to determine whether this signature has therapeutic promise as an anti-AML target.…”
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Lung Ultrasound Score for Prediction of Weaning Outcome From Mechanical Ventilation by Farouk Mostafa Faris, Ayman Atef Sarabana, Kamel Mohamed abd elwahab, Mahmoud Saad Nawar

“…Abstract Introduction Failure of extubation of patients on mechanical ventilation is one of the common problems in the intensive care unit (ICU). Aim of work To evaluate the validity of lung ultrasound score in prediction of weaning outcomes and postextubation distress. …”
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Effect of milk recording scheme on lactation milk yields prediction accuracy by Dragomir Kompan, Drago Solić, Nikola Raguž, Sonja Jovanovac, Vesna Gantner

“…The Test Interval Method (TIM) was used for prediction of lactation values. …”
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In silico prediction of multi-epitope vaccine candidates against Mycobacterium leprae by Almas Shabrina, Asep Iin Nur Indra, Sonny Feisal Rinaldi, Fusvita Merdekawati

“…The vaccine candidate was also predicted to be stable, antigenic, non-allergenic, non-toxic, and hydrophilic. …”
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Predicting The Feasibility of Small Bowel Feeding in Patients With Generalized Secondary Peritonitis by O. G. Sivkov

“…Finding a simple reproducible routine test is relevant for the determination of post-pyloric feeding tolerance.Aim. To evaluate in a pilot study the usefulness of acetaminophen absorption test with post-pyloric drug administration in patients with generalized secondary peritonitis.Materials and methods. …”
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Machine Learning for Prediction of Relapses in Multiple Drug Resistant Tuberculosis Patients by A. S. Аlliluev, O. V. Filinyuk, E. E. Shnаyder, S. V. Аksenov

“…The objective of the study: to evaluate the possibility of using machine learning algorithms for prediction of relapses in multiple drug resistant tuberculosis (MDR TB) patients.Subjects and Methods. …”
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Development and Validation of a Dynamic Prediction Model for Massive Hemorrhage in Trauma by Chengyu Guo, Maolin Tian, Minghui Gong, Fei Pan, Hui Han, Chunping Li, Tanshi Li

“…Models were evaluated in terms of accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and the area under the curve (AUC). …”
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ARTIFICIAL LEARNING BASED ON KERNEL SVM FOR THE PREDICTION OF CARDIOVASCULAR DISEASE HYPERTENSION by Patient MUSUBAO SWAMBI, Albert Ntumba Nkongolo, Pierre Kafunda Katalay, Rostin Mabela Matendo Makengo, Eugène Mbuyi Mukendi

“…The research utilizes a diverse dataset that includes demographic, physiological, and lifestyle variables, applying kernel SVM to predict hypertension outcomes. Performance is evaluated through rigorous cross-validation, with metrics including accuracy, precision, recall, and F1-score. …”
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Deep learning can predict cardiovascular events from liver imaging by Gregory Patrick Veldhuizen, Tim Lenz, Didem Cifci, Marko van Treeck, Jan Clusmann, Yazhou Chen, Carolin V. Schneider, Tom Luedde, Peter W. de Leeuw, Ali El-Armouche, Daniel Truhn, Jakob Nikolas Kather

“…The F-statistic from the one-way ANOVA comparing the Systematic Coronary Risk Evaluation 2 (SCORE2) values of the three prediction model score groups was 68.49 with p <0.001. …”
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Scalable machine learning framework for predicting critical links in urban networks by Nourhan Bachir, Chamseddine Zaki, Hassan Harb, Roland Billen

“…The inclusion of dynamic traffic metrics and advanced preprocessing techniques further enhanced predictive accuracy and generalization capabilities. …”
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Multiple entropy fusion predicts driver fatigue using forehead EEG by Renyu Yang, Ling Zhang, Renhuan Yang, Lixing Hou, Donglong Zhu, Boming Zhong

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Widespread asymmetries of amygdala nuclei predict auditory verbal hallucinations in schizophrenia by Magda L. Dumitru, Erik Johnsen, Rune A. Kroken, Else-Marie Løberg, Lin Lilleskare, Lars Ersland, Kenneth Hugdahl

“…Brain asymmetries have also been linked to the condition, but the relevance of asymmetries within the amygdala, which coordinates all emotional signals, to the content of and response to auditory verbal hallucinations has not been explored. Methods We evaluated the performance of two asymmetry biomarkers that were recently introduced in literature: the distance index, which captures global asymmetries, and a revised version of the laterality index, which captures left–right local asymmetries. …”
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OPUS-BFactor: Predicting Protein B-Factor with Sequence and Structure Information by Yulu Yang, Ying Lv, Zhenwei Luo, Qinghua Wang, Gang Xu, Jianpeng Ma

“…Evaluation on three test sets, including recently released targets from CAMEO and CASP15, demonstrated that OPUS-BFactor significantly outperformed other B-factor prediction methods. …”
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Insulin dependence predicts adverse outcomes following lumbar spine surgery by Haseeb E. Goheer, Alden H. Newcomb, Zachary M. Johnson, Christopher G. Hendrix, Alexander R. Garcia, Brian Q. Truong, Jonathan J. Carmouche

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Parenclitic network mapping predicts survival in critically ill patients with sepsis by Emily Ito, Tope Oyelade, Matthew Wikner, Jinyuan Liu, Watjana Lilaonitkul, Ali R. Mani

“…However, mapping functional connectivity for individual patients has been challenging due to the lack of analytical methods for evaluating physiological networks using routine clinical and laboratory data. …”
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Utility of blood parameters in predicting oesophageal varices in patients with liver cirrhosis by Cyrin Annie Cyriac, Geeta Achutha Panicker, Sojan George Kunnathuparambil, Steffin Mathai Kattoor

“…Background: This study aimed to evaluate the utility of various blood parameters in predicting oesophageal varices in patients with cirrhosis of liver. …”
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Scoping review of the use of multimorbidity variables in cardiovascular disease risk prediction by Emma Church, Katrina Poppe, Susan Wells

“…Future research is needed to evaluate the incremental value of multimorbidity indices in cardiovascular disease risk prediction models to inform risk stratification and management strategies in people with multimorbidity.…”
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