Urinary Albumin-to-Creatinine Ratio (uACR) Point-of-Care (POC) Device with Seamless Data Transmission for Monitoring the Progression of Chronic Kidney Disease by Artitaya Thiengsusuk, Napaporn Youngvises, Runtikan Pochairach, Rehab Osman Taha, Kridsada Sirisabhabhorn, Nadda Muhamad, Wanchai Meesiri, Wanna Chaijaroenkul, Kesara Na-Bangchang

“…The PPV (positive predictive value) was 100%, indicating perfect identification of patients with severe nephropathy (uACR > 300 mg/g creatinine). …”
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A novel ubiquitin-related genes-based signature demonstrated values in prognostic prediction, immune landscape sculpture and therapeutic options in laryngeal cancer by Lu Liu, Lu Liu, Lu Liu, Lu Liu, Bing Wang, Xiaoya Ma, Xiaoya Ma, Lei Tan, Lei Tan, Lei Tan, Xudong Wei, Xudong Wei

“…The nomogram showed higher predictive value and net clinical benefit than traditional indicators. …”
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Evaluation of Plasma Soluble Cd40 Ligand Levels in Children with Familial Mediterranean Fever and Its Relationship with Carotid Intima–Media Thickness by Sukriye Ozde, Cansu Mehdizade, Ozel Mehmet Ali, Cem Ozde, Osman Kayapinar, Muferret Erguven

“…This analysis demonstrated that sCD40L levels exceeding 100 pg/mL were predictive of FMF, yielding a sensitivity of 70.6% and a specificity of 62.3%. The positive predictive value and negative predictive value were 55.4% and 64.3%, respectively. …”
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Phase angle as a predictor of motor function decline in children with Duchenne muscular dystrophy by Qin Hu, Xiaoyong Chen, Shaojie Luo, Yanhong Wang, Peicong Fan, Xiaona Wu, Hui Zhou, Huayan Xu, Na Li, Xiaotang Cai

“…PhAs in legs demonstrate the strongest correlation and highest predictive value for lower limb motor function loss(AUC from 0.725 to 0.863). …”
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ERCC1 as a Marker of Ovarian Cancer Resistance to Platinum Drugs by T. A. Bogush, A. S. Popova, E. A. Dudko, E. A. Bogush, A. S. Tyulyandina, S. A. Tyulyandin, M. I. Davydov

“…Data on the prognostic and predictive value of ERCC1 as a marker of the response to platinum-based therapy in ovarian cancer are systematized. …”
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Incremental Prognostic Value of Hippocampal Metabolic Activity for Sudden Cardiac Death in Patients With Heart Failure With Reduced Ejection Fraction by Zhiyong Shi, Mingkai Yun, Binbin Nie, Yujie Bai, Yaqi Zheng, Enjun Zhu, Yuetao Wang, Marcus Hacker, Yongqiang Lai, Baoci Shan, Sijin Li, Xiaoli Zhang, Xiang Li

“…Background Hippocampal injury is linked to cognitive impairment and cardiac events in patients with heart failure with reduced ejection fraction. However, the predictive value of hippocampal metabolic activity (HMA) for sudden cardiac death (SCD) and the underlying mechanisms remain unclear. …”
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Bowel viability assessment during surgery (review of the literature) by A. A. Zacharenko, M. A. Belyaev, A. A. Trushin, D. A. Zaytcev, R. V. Kursenko

“…Parameters of techniques are analyzed: intraoperative clinical application, invasiveness, objectivity and quantification of viability parameters, predictive value for necrosis and anastomotic leakage. …”
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Myocardium-to-cavity ratio derived from simultaneous 99mTc-PYP/201Tl dual-isotope SPECT imaging to differentially diagnose transthyretin cardiac amyloidosis by Shozo Yamashita, Kenichi Nakajima, Teppei Kitano, Hiromu Kato, Tatsuya Yoneyama, Haruki Yamamoto, Kunihiko Yokoyama

“…The M/C ratio demonstrated 100% sensitivity, specificity, and predictive values, irrespective of imaging time. In contrast, the H/CL ratios showed 100% sensitivity, 95% specificity, 79% positive predictive value, and 100% negative predictive value. …”
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VISCERAL ADIPOSITY AS A GLOBAL FACTOR OF CARDIOVASCULAR RISK by G. A. Chumakova, T. Yu. Kuznetsova, M. A. Druzhilov, N. G. Veselovskaya

“…On the other hand, the two most global problems of this relationship — “obesity paradox” and heterogeneity of obesity phenotypes by cardiometabolic risk, released multiple discussions on the issues of predictive value of body overweight and obesity, and worth of correction in patients under the secondary prevention framework. …”
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Genetic Predisposition to Sporadic Cancer: How to Handle Major Effects of Minor Genes? by Remond J. A. Fijneman

“…As a consequence, although allelic variation in one TSG on a permissive genetic Background can have major effects on tumor development, the net effect of allelic variation in multiple interacting TSGs remains hard to predict. Therefore, the predictive value of SNP-analysis to estimate an individuals cancer risk will be restricted to those TSGs that exhibit single-gene effects. …”
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The validity of monitoring the control of diabetes with random blood glucose testing by O.F. Daramola, B. Mash

“…Retrospective data from a district hospital setting were used to analyse the correlation between glycated haemoglobin (HbA1c) and RBG, the best predictive value of RBG, and its predictive properties. …”
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Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank by Heli Julkunen, Juho Rousu

“…In a clinical cardiovascular risk prediction scenario using the established QRISK3 model, the method adds predictive value by identifying interactions beyond the age interaction effects currently included. …”
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Improving  the  Financial  Reporting of  Organizations  in the Digital Economy by T. Yu. Druzhilovskaya, E. S. Druzhilovskaya

“…The article analyzes the problem of the relationship between the development of the digital economy and ensuring the qualitative characteristics of financial statements, such as relevance, predictive value, confirming value, materiality, fair representation, completeness, neutrality, comparability, verifiability, timeliness, clarity and being error-free. …”
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Predictors for Gangrene and Perforation of Gallbladder Wall in Patients with Acute Cholecystitis by Polina Marinova

“…The total possible score was 11 points. The positive predictive value of the scale was 96% and identified the cases with micro-perforation and perivesical abbesses among the group with the highest total score.…”
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Diagnostic Utility of Endocan and Interleukins for Late-Onset Neonatal Sepsis by Preslava Gatseva, Alexander Blazhev, Zarko Yordanov, Victoria Atanasova

“…The best sensitivity (78%) and negative predictive value (84%) was found for IL-6. The introduction into routine practice of indicators such as PCT and IL-6 may provide an opportunity to promptly optimize the diagnostic and therapeutic approach to LOS.…”
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Relevance of telemonitoring algorithms for the management of home noninvasive ventilation by Clara Bianquis, Kinan El Husseini, Léa Razakamanantsoa, Adrien Kerfourn, Emeline Fresnel, Jean-Christian Borel, Antoine Cuvelier, Johan Dupuis, Frédéric Gagnadoux, Capucine Morélot-Panzini, Jesus Gonzalez-Bermejo, Jean-François Muir, Arnaud Prigent, Claudio Rabec, Wojciech Trzepizur, Joao Winck, Patrick Brian Murphy, Maxime Patout

“…They had a global sensitivity of 78% (95% CI 37–95%), a specificity of 40% (95% CI 19–78%), a positive predictive value of 72% (95% CI 65–77%) and a negative predictive value of 45% (95% CI 37–51%). …”
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The contributions of brain structural and functional variance in predicting age, sex and treatment by Ning-Xuan Chen, Gui Fu, Xiao Chen, Le Li, Michael P. Milham, Su Lui, Chao-Gan Yan

“…We found that voxel-based structural indices had stronger predictive value for age and sex, while voxel-based functional metrics showed stronger predictive value for treatment. …”
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Assessing the performance of the Iceland screens, treats, or prevents multiple myeloma (iStopMM) model in a multicultural Bronx cohort: implications for monoclonal gammopathy of un... by Rajvi Gor, Jeevan Shivakumar, Pallavi Surana, John Wei, Irina Murakhovskaya, Mendel Goldfinger, Noah Kornblum, Lauren Shapiro, Aditi Shastri, Ridhi Gupta, David Levitz, Marina Konopleva, Eric Feldman, Kira Gritsman, R. Alejandro Sica, Ioannis Mantzaris, Amit Verma, Dennis Cooper, Murali Janakiram, Nishi Shah

“…The area under the receiver operating characteristic (AUROC) curve assessed the iStopMM model’s performance in predicting ≥10% plasma cells, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. …”
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Personalised prediction of maintenance dialysis initiation in patients with chronic kidney disease stages 3–5: a multicentre study using the machine learning approach by Usman Iqbal, Tzu-Hao Chang, Chu-Lin Chou, Mai-Szu Wu, Yung-Ho Hsu, Chih-Wei Huang, Anh Trung Hoang, Phung-Anh Nguyen, Thanh Phuc Phan, Gia Tuyen Do, Huu Dung Nguyen, I-Jen Chiu, Yu-Chen Ko, Chia-Te Liao

“…Model evaluation metrics, including area under the curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value and F1 score, were employed.Results A total of 6123 and 5279 patients were included for 1 year and 3 years of the model development. …”
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Research on Nonlinear Time Series Processing Method for Automatic Building Construction Management by Yunbing Liu

“…By comparing the results, the maximum relative error of BP network prediction is 18.59%, while the maximum relative error of RBF network prediction is 29.16%, and the average relative error of 13P network prediction is 7.02%, while the average relative error of RBF network prediction value is 10.5%. The comprehensive error of network prediction is 6.1%, RBF network prediction is 8.52%, the standard deviation RMSE of BP network prediction error is 15.347, and that of RBF network prediction error is 21.401, and it shows that the prediction accuracy of BP network is higher than that of RBF network.…”
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