Postoperative improvement in the index finger center of pressure trajectory during precision grip in patients with degenerative cervical myelopathy. by Duy Quoc Vo, Lu Zhang, Naoto Noguchi, Ken Kondo, Ryoto Akiyama, Hiroshi Fujii, Yuki Obokata, Bumsuk Lee

“…A multiple regression analysis was used to identify the predictive value of the pre-operative COP trajectory to the severity of sensorimotor dysfunction.…”
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An Observational Study on Pre-natal Diagnosis of Congenital Talipes Equinovarus by Gaurav Vatsa, Saurabh Suman, Siddharth Kumar Singh

“…Diagnostic accuracy metrics, including sensitivity, specificity, and predictive values, were calculated. Results: Among live births, pre-natal US identified CTEV cases, with final confirmation distinguishing structural from positional deformities. …”
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ALGORITHM FOR ASSESSING TIME AND COST RISKS AT ENTERPRISES OF THE MILITARY-INDUSTRIAL COMPLEX by N.D. Pechalin, A.G. Finogeev

“…The risk analysis algorithm solves the problems of assessing the time and cost parameters of the project task for compliance with the predicted values at an early stage of the production cycle. …”

Predict of the development of lipid distress syndrome in patients with a sustained response to antiviral therapy of chronic hepatitis C by D. Yu. Konstantinov, G. V. Nedugov

“…The sensitivity, specificity, predictive value of positive and. negative results of forecasting and precision index developed forecasting model of Fisher discriminant lipid, distress syndrome equal 100%. …”
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Investigating the correlation between ultrasonic pulse velocity and compressive strength in polyurethane foam concrete by R. Roobankumar, M. SenthilPandian

“…The empirical relationships between compressive strength and UPV were found to be exponential, with high correlation values ranging from 0.9012 to 0.9998. The predicted values and the experimentally measured results were compared in order to confirm the accuracy of the empirical equations for compressive strength prediction.…”
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Mental health literacy and help-seeking: the mediating role of self-stigma and emotional intelligence by Mahd Awan, Melissa A. Boyce, Brittany L. Lindsay

“…The current study examined the predictive value of mental health literacy with respect to both formal and informal help-seeking intentions. …”
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Verification of subclinical carotid atherosclerosis as part of risk stratification in overweight and obesity: the role of machine learning in the development of a diagnostic algori... by M. A. Druzhilov, T. Yu. Kuznetsova, D. V. Gavrilov, A. V. Gusev

“…Mathematical models created using ML methods are characterized by a predictive value from 75 to 97% with a sensitivity of 77 to 92% and a specificity of 80 to 98%.Conclusion. …”
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Investigating Torsin‐1A‐interacting protein 1 as a predictive and immunological biomarker in cancer by Gurleen Kaur, Gurparsad Singh Suri, Dheeraj Shinde

“…The results of our study highlight the potential predictive value of TOR1AIP1 in cancer prognosis and therapy. …”
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POWER DOPPLER IMAGING IN PATIENTS WITH SUSPECTED PROSTATE CANCER by T. V. Shatylko, L. N. Sedova, A. Yu. Korolev

“…Sensitivity of power Doppler imaging was 82.4%, specificity was 70.5%, positive and negative predictive values were 66.7% and 72.3% correspondingly. …”
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Comparing random forest flood frequency analysis with regional flood frequency, Creager and SCS in Doab-Qazanchi, Kermanshah by Maryam Hafezparast, Sadaf Gord, Rasool Ghobadian

“…The SCS method was implemented for the flood on 03/04/2019 and it showed that the occurred flood is equivalent to a 25-year flood in this region. The predicted values estimated a lower discharge than the soil conservation service (SCS) method. …”
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A novel XAI framework for explainable AI-ECG using generative counterfactual XAI (GCX) by Jong-Hwan Jang, Yong-Yeon Jo, Sora Kang, Jeong Min Son, Hak Seung Lee, Joon-myoung Kwon, Min Sung Lee

“…In contrast, the proposed framework explores “what-if” scenarios, generating counterfactual ECGs that increase or decrease a model’s predictive values. This approach has the potential to increase clinicians’ trust specific changes—such as increased T wave amplitude or PR interval prolongation—influence the model’s decisions. …”
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Clinical and X-ray Diagnosis of Respiratory Distress in Premature Babies of Less than 34-Week Gestational Age by N. N. Volodin, D. N. Degtyarev, I. Ye Kotik, I. S. Ivanova

“…A clear distinction of two types of the X-ray pattern of RDS in very premature babies may be of great predictive value.…”
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Study on cutting force in laser-assisted ultrasonic elliptical vibration machining (LUEVM) of high volume SiCp/Al composites by Peicheng Peng, Tian Tian, Heshuai Yu, Daohui Xiang, Ke Niu, Wei Gao, Yanqin Li, Zhaojie Yuan, Guofu Gao

“…The results show that the predicted value matches the experimental value well, and the maximum error is 18.2 %. …”
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A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting by Zongxi Qu, Kequan Zhang, Jianzhou Wang, Wenyu Zhang, Wennan Leng

“…In this model, the original wind speed data is firstly divided into a finite set of signal components by ensemble empirical mode decomposition, and then each signal is predicted by several artificial intelligence models with optimized parameters by using the fruit fly optimization algorithm and the final prediction values were obtained by reconstructing the refined series. …”
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COMPARISON OF WEIGHTED MARKOV CHAIN AND FUZZY TIME SERIES-MARKOV CHAIN METHODS IN AIR TEMPERATURE PREDICTION IN BANDA ACEH CITY by Siti Rusdiana, Diana Febriana, Ikhsan Maulidi, Vina Apriliani

“…The prediction results of air temperature in Banda Aceh city using the FTS-MC method for the next three weeks obtained predicted values of 26,66℃ for the 105th week, 26,79℃ for the 106th week, and 26,83℃ for the 107th week. …”
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Optimizing Concrete Mix Design for Cost and Carbon Reduction Using Machine Learning by Angga T. Yudhistira, Arief S. B. Nugroho, Iman Satyarno, Tantri N. Handayani, Malindu Sandanayake, Rimba Erlangga, Jonathan Lianto, Alfa Rosyid Ernanto

“…The research findings indicate that the ML model provides satisfactory prediction values with an R2 value of 0.9043, root mean square error of 48.5147 and mean absolute percentage error of 0.0484. …”
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Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery by W. Scott Watkins, Edgar J. Hernandez, Thomas A. Miller, Nathan R. Blue, Raquel Mae Zimmerman, Eric R. Griffiths, Erwin Frise, Daniel Bernstein, Marko T. Boskovski, Martina Brueckner, Wendy K. Chung, J. William Gaynor, Bruce D. Gelb, Elizabeth Goldmuntz, Peter J. Gruber, Jane W. Newburger, Amy E. Roberts, Sarah U. Morton, John E. Mayer, Christine E. Seidman, Jonathan G. Seidman, Yufeng Shen, Michael Wagner, H. Joseph Yost, Mark Yandell, Martin Tristani-Firouzi

“…Here, we use artificial intelligence (AI) technologies to explore the predictive value of whole exome sequencing in forecasting clinical outcomes following surgery for congenital heart defects (CHD). …”
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PTSD course and predictors in a 15 year longitudinal cohort following suspected serious injury by Jeanet F. Karchoud, Chris M. Hoeboer, Irina Karaban, Joanne Mouthaan, Marit Sijbrandij, Miranda Olff, Rens van de Schoot, Mirjam van Zuiden

“…Early post-trauma predictors had predictive value up to 12–15 years. This suggests that early risk identification of one-year PTSD and subsequent effective early interventions also hold long-term beneficial effects for PTSD outcome.…”
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Methodology Based on BERT (Bidirectional Encoder Representations from Transformers) to Improve Solar Irradiance Prediction of Deep Learning Models Trained with Time Series of Spati... by Llinet Benavides-Cesar, Miguel-Ángel Manso-Callejo, Calimanut-Ionut Cira

“…In this study, we propose a novel end-to-end methodology for solar irradiance forecasting that starts with the search for the data and all of the preprocessing operations involved in obtaining a quality dataset, continuing by imputing missing data with the BERT (Bidirectional Encoder Representations from Transformers) model, and ending with obtaining and evaluating the predicted values. This novel methodology is based on three phases; namely, Phase_1, related to the acquisition and preparation of the data, Phase_2, related to the proposed imputation with a BERT model, and Phase_3, related to the training and prediction with new models based on deep learning. …”
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ST-GAT Resident OD Prediction Model Based on Mobile Signaling Data by Xianguang Jia, Weijie Fang, Yingying Lyu, Jinke Zhang, Mengyi Guo, Dong Li, Jie Qu, Fengxiang Guo

“…In this paper, this model is compared with the existing ST-GCN, DMS, GMM, PSAM-CNN, ST-Transformer, and COMD models, and the experimental results show that the predicted values of the ST-GAT model have a significant improvement in the prediction accuracy compared to other models. …”
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