Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

“…We systematically reviewed COVID-19 ML prediction models developed under the background of the epidemic using the PRISMA method. …”
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Inflammatory and demographic determinants of elevated white blood cell counts: insights from predictive modeling and NHANES analysis by Saanie Sulley, Yan Zhou, Memory Ndanga

“…These results underscore the significance of tailored methods in hematologic and inflammatory evaluations, affecting the enhancement of diagnostics and the minimization of health inequalities. …”
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Prediction of strength parameters of concrete containing different additives using optimized neural network algorithm by Behzad Haseli, Gholamreza Nouri, Meysam Mardi, Ehsan Adili, Mohammad Bahari

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Morphometry in the cytological evaluation of breast lesions and its diagnostic significance by Sujata Jetley, Beenish Bano, Shaan Khetrapal, Safia Rana, Zeeba S. Jairajpuri, Ajay Thakral, Arushi Gupta

“…Background: Fine-needle aspiration cytology is the primary method for evaluating patients with palpable breast lumps. …”
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Evaluation of plasma miRNA107 in Egyptian hypertensive patients by Ayat K.A. Esmail, Seham M.S. El Nakeeb, Fatma M. El-Senosy, Areej M.R. Mohammad, Rasha E.M.A. El Aziz

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Novel predictive role of glomerular filtration rate in atrial fibrillation development among chronic heart failure patients by Xuhui Hong, Wenhui Xie, Xiaohong Lin

“…The calibration curve of the constructed nomogram model demonstrated an excellent fit, showing good consistency between the predicted and actual AF risks, thus indicating that the model has strong predictive capability.…”
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Predictive study of machine learning combined with serum Neuregulin 4 levels for hyperthyroidism in type II diabetes mellitus by Huilan Gu, Ye Lu

“…Machine learning techniques have garnered widespread attention due to their advantages in modeling high-dimensional, heterogeneous data.ObjectiveThis study was to evaluate the predictive capability of a support vector machine (SVM) model based on serum NRG4 combined with a convolutional neural network (CNN) and long short-term memory network (LSTM)-based ultrasound feature classification (SVM-CNN+LSTM) model for predicting the occurrence of FT in patients with T2DM.MethodsStudied 500 T2DM patients (60 with FT, 440 without), and 200 healthy controls. …”
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Development and Evaluation of a Computable Phenotype for Normal Tension Glaucoma by Fountane Chan, MD, Wei-Chun Lin, MD, PhD, Alan Tang, Benjamin Y. Xu, MD, PhD, Sophia Y. Wang, MD, MS, Michael V. Boland, MD, PhD, Catherine Q. Sun, MD, Sally Baxter, MD, MSc, Brian Stagg, MD, MS, Michelle Hribar, PhD, Aiyin Chen, MD

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Machine Learning in E-Commerce: Trends, Applications, and Future Challenges by Elias Dritsas, Maria Trigka

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A study on predicting the risk of coronary artery disease in OSAHS patients based on a four-variable screening tool potential predictive model and its correlation with the severity... by Yanli Yao, Yu Li, Yulan Chen, Xuan Qiu, Gulimire Aimaiti, Ayiguzaili Maimaitimin

“…ObjectiveThis study aims to evaluate the potential association between the four-variable screening tool (the 4 V) potential predictive model in predicting coronary artery disease (CAD) risk in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) and its correlation with the severity of coronary atherosclerosis, as measured by the Gensini scoring system.Methods1197 OSAHS patients with suspected CAD who were hospitalized in the First Affiliated Hospital of Xinjiang Medical University between March 2020 and February 2024 were selected. …”
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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Discharge routing is a key method for predicting downstream hydrograph in canals or rivers. …”
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Predictive value of color doppler neuro-sonography for the development of neurological sequels in newborn infants with hypoxic ischemic encephalopathy by Vasiljević Brankica, Maglajlić-Đukić Svjetlana, Stanković Sanja, Lutovac Dragana, Gojnić Miroslava

“…The aim of this study was to evaluate the predictive value of cD-US for abnormal neurodevelopmental outcome in the neonates with HIE. …”
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Multi-centre evaluation of Gram stain in the diagnosis of septic arthritis by C. Smith, R. J. Maloney, D. Wearmouth, H. Sharma, K. Saeed, K. Saeed, N. Ahmad-Saeed, R. Annett, L. Barrett, S. E. Boyd, S. E. Boyd, S. E. Boyd, P. Davies, H. Hughes, G. Jones, L. Leach, M. Lynch, D. Nayar, M. Marsh, S. Mitchell, L. Moffat, L. S. P. Moore, L. S. P. Moore, L. S. P. Moore, M. E. Murphy, M. E. Murphy, S. A. O'Shea, T. Peach, C. Petridou, N. Reidy, B. Talbot, C. Aldridge, G. Barlow, G. Barlow

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Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF by Andrea Asperti, Gabriele Raciti, Elisabetta Ronchieri, Daniele Cesini

“…The results demonstrate the effectiveness of these methods, not only in predicting anomalies but also in pinpointing critical areas within monitored metrics. …”
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Predictive value of platelet parameters and peripheral blood cell ratios for abdominal aortic calcification of peritoneal dialysis patients by Zhao Shi-zhu, Cao Jing-yuan, Cao Pei-yang, Lu Guo-yuan

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Predictive factors of quality of life in temporal and extratemporal lobe epilepsy: association with affective temperament profiles and psychiatric comorbidities by Sehnaz Basaran, Halil İbrahim Tas

“…Affective temperaments were evaluated using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Autoquestionnaire (TEMPS-A). …”
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Research on Intelligent Vehicle Tracking Control and Energy Consumption Optimization Based on Dilated Convolutional Model Predictive Control by Lanxin Li, Wenhui Pei, Qi Zhang

“…Finally, a co-simulation environment based on CarSim and Simulink was used to evaluate the proposed method. Comparative analyses with a traditional MPC and a neural network-based MPC (NNMPC) demonstrated that the DCMPC consistently exhibited superior trajectory tracking performance under various test scenarios. …”
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Generative artificial intelligence for sustainable development: predictive trend analysis in key sectors using natural language processing by Chetan Sharma, Shamneesh Sharma, Vivek Bhardwaj, Balwinder Kaur Dhaliwal

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Quality Management in Chemical Processes Through Fuzzy Analysis: A Fuzzy C-Means and Predictive Models Approach by Gabriel Marín Díaz

“…Experimental validation using a real-world white wine dataset, evaluated in terms of accuracy and interpretability, shows that the proposed model outperforms traditional approaches in both predictive performance and transparency. …”
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Comparative analysis of machine learning algorithms for predicting tibial intramedullary nail length from patient characteristics by Yujian Hui, Hengda Hu, Jinghua Xiang, Xingye Du

“…Abstract Objective This study aimed to evaluate the performance of five machine learning algorithms in predicting tibial intramedullary nail length using patient demographic data (gender, height, age, and weight), with the goal of developing a clinically relevant and accurate predictive model. …”
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