Validation of an Automated High-Throughput Multiplex Real-Time PCR Assay for Detection of Enteric Protozoa by Rachel Lau, Jason Kwan, Kimberley Marks-Beaubrun, Ruben Cudiamat, Min Qun Ellen Chen, Krista Orejana, Filip Ralevski, Andrea K. Boggild

“…<b>Results</b>: Among 461 unpreserved fecal specimens, sensitivity, specificity, positive predictive and negative predictive values of the enteric multiplex for fresh specimens were as follows: 93%, 98.3%, 85.1%, 99.3% for Bh; 100% for all measures in <i>Cryptosporidium</i> and Cc; 100%, 99.3%, 88.5%, 100% for Df; 33.3%, 100%, 100%, 99.6% for Eh; and 100%, 98.9%, 68.8%, 100% for Gl, respectively. …”
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Unveiling the Microbial Symphony of Amasi: A Targeted Metagenomic 16S rRNA, ITS, and Metabolites Insights Using Bovine and Caprine Milk by Betty Olusola Ajibade, Titilayo Adenike Ajayeoba, Saheed Sabiu, Konstantin V. Moiseenko, Sizwe Vincent Mbona, Errol D. Cason, Tatyana V. Fedorova, Oluwatosin Ademola Ijabadeniyi

“…It was found that the amino acid and drug metabolism pathway prediction values in Amasi samples were significantly higher (<i>p</i> < 0.05) than in raw cow and goat milk, according to the inferred analysis (PICRUSt). …”
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Evaluation of Noninvasive Adjuncts for Early Detection of Oral Cancer in Oral Potentially Malignant Disorders and Development of Risk-Based Management Strategies: Protocol for a Pr... by Ruchika Gupta, Apurva Ratnu, Shalini R Gupta, Hariprakash Hadial, Lucky Singh, Prashant Kumar Singh, Shalini Singh

“…Sensitivity, specificity, and negative and positive predictive values of these adjunctive techniques (autofluorescence and TB) in the detection of oral cancer shall be calculated using biopsy as the gold standard. …”
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Improving prediction accuracy of hospital arrival vital signs using a multi-output machine learning model: a retrospective study of JSAS-registry data by Yasuyuki Kawai, Koji Yamamoto, Keisuke Tsuruta, Keita Miyazaki, Hideki Asai, Hidetada Fukushima

“…Model performance was assessed by comparing the predicted values with the actual hospital arrival measurements using mean absolute error, R² score, residual standard deviation, and Spearman’s correlation coefficient. …”
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Development and validation of a prediction model for the risk of citrate accumulation in critically ill patients with citrate anticoagulation for continuous renal replacement thera... by Zhi-Qing Hu, Zheng-Long Ye, Hui Zou, Shang-Xiang Liu, Cheng-Qing Mei

“…The calibration curves in the training set and internal/external validation sets showed a high degree of consistency between predicted values and observed values (according to the Hosmer-Lemeshow test, the P-values were 0.7673, 0.2401, and 0.4512 for the training set, internal validation set, and external validation set, respectively). …”
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Prediction of grey mould disease from greenhouse tomato based on radical basis function neural network by Zhang Zhi, Hu Xiaohui, Zou Zhirong

“…The results of fitting testing of experimental data from other 12 samples with the obtained model showed that the predicted values of 10 samples about grey mould disease grade were the same with their actual values, while one grade higher than actual value could be seen in other two samples. …”
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Identification of High-Photosynthetic-Efficiency Wheat Varieties Based on Multi-Source Remote Sensing from UAVs by Weiyi Feng, Yubin Lan, Hongjian Zhao, Zhicheng Tang, Wenyu Peng, Hailong Che, Junke Zhu

“…Furthermore, the research conducted principal component analysis (PCA) and membership function analysis on the predicted values of the optimal models for each indicator, established a comprehensive evaluation index for high photosynthetic efficiency, and employed cluster analysis to screen the test materials. …”
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Performance of Xpert MTB/RIF and acid-fast bacilli smear microscopy for the diagnosis of pulmonary tuberculosis using bronchoalveolar lavage samples in negative or sputum-scarce ad... by Vanessa Sabella-Jiménez, Valentina L. Sabella-Jiménez, Valentina Restrepo-Espinosa, Juanita Eljadue-Flórez, Claredit Valentina Gallardo-Castro, Andrea Alexandra Silvera, Carlos Otero-Herrera, Hugo Andrés Macareno Arroyo, Jorge Acosta-Reyes, Jorge Luis Quintero Barrios

“…Validity criteria was evaluated by sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and Cohen’s kappa with their 95% confidence intervals using Wilson’s score method by OpenEpi Version 3.01. …”
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Prediction Equation for Spirometric Parameters in Cairo Governorate Adult Population by Omar M. A. Abdelzaher, Gamal A. Salem, Ashraf A. Elmaraghy

“…This study compared the international reference figures of mean predicted spirometry values with our derived predicted values of lung function parameters. Results: The predicted equations for FEV1 were [(3.429+(-0.028*Age)+(-0.017*weight)+(0.018*height)], and [1.238+(-0.005*Age)+(-0.006*weight)+(0.014*height)] for males and females respectively. …”
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Gluten Contamination of Labelled Gluten-Free Food Products Marketed in China by Yanjun Li, Qing Liu, Samuel Godefroy, Jingguang Li, Yan Chen

“…However, when the threshold was 10 mg/kg and 5 mg/kg, the McNemar <i>x</i>² test showed significant differences between the proportions of positive results of the two ELISA platforms and R5 Méndez (<i>p</i>-value < 0.05); using R5 Méndez as the reference, the two ELISA platforms showed 53.1% to 70.3% positive predictive values, suffering the drawback of high false-positive results. …”
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Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational... by Jenny Mathew, Jaclyn A Pagliaro, Sathyanarayanan Elumalai, Lauren K Wash, Ka Ly, Alison J Leibowitz, Varsha G Vimalananda

“…Using appropriate algorithmic techniques, the study expects the model to have a sensitivity of >80% and a positive predicted value of >70%. ResultsRecruitment began in January 2023, and at the time of manuscript submission, 204 patients have been enrolled. …”
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Projected changes and burden of type 2 diabetes in China from 1990 to 2021: an analysis of GBD 2021 data by Junhao MA, Guangqiang MIAO, Guixiao WANG, Shen LI, Liping YANG

“…The dynamic trends of the predicted values of the ARIMA model, NNAR model, and combined ARIMA-NNAR model were basically consistent with the actual situation, but the values of each evaluation index of the combined prediction model showed that the prediction effect was better than that of the single prediction model. …”
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Multicenter development of a deep learning radiomics and dosiomics nomogram to predict radiation pneumonia risk in non-small cell lung cancer by Xun Wang, Aiping Zhang, Huipeng Yang, Guqing Zhang, Junli Ma, Shucheng Ye, Shuang Ge

“…The calibration curve showed that the predicted value of DLRDN was in good agreement with the actual value. …”
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Corneal subepithelial nerve fibers in type 2 diabetes: potential biomarker of diabetic neuropathy by Ling-Rui Meng, Hua Chen, Wen-Qian Chen, Yi Gao, Zi-Wei Li, Zi Ye, Zhao-Hui Li

“…The AUC of the ROC curve under the logistic regression model also demonstrated good predictive values. The cut-off values of CNFD, CNFL, and main branch length density for diabetes showed 31.25, 18.85, and 12.56, respectively. …”
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Investigation of the Effects of Different Plyometric Training Protocols on Punching Force and Muscle Performance in Male Boxers by Mehmet Söyler, Alper Cenk Gürkan, İdris Kayantaş, Serhat Aydın, Baykal Karataş, Meriç Eraslan, Musa Şahin, Hamza Küçük, Adela Badau, Dana Badau

“…Adjusting for the strength-to-weight ratio significantly influenced the predictive values in intergroup comparisons (<i>p</i> < 0.005). …”
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Evaluation of the fluorescent-thin layer chromatography (f-TLC) for the diagnosis of Buruli ulcer disease in Ghana. by Richard K Amewu, Gideon Atinga Akolgo, Millicent Esi Asare, Zigli Abdulai, Anthony S Ablordey, Kingsley Asiedu

“…The positive (PPV) and negative (NPV) predictive values, area under the receiver operating characteristic curve Azevedo et al. (2014), and diagnostic odds ratio were used to assess the predictive accuracy of the f-TLC method. …”
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Analysis of factors affecting the accuracy of 18F-fluorodeoxyglucose positron emission tomography combined with computed tomography in case of suspected prosthetic valve infective... by I. P. Aslanidi, E. Z. Golukhova, D. M. Pursanova, O. V. Mukhortova, I. V. Shurupova, I. V. Ekaeva, T. A. Katunina, T. A. Trifonova

“…Thus, the sensitivity, specificity and diagnostic accuracy of PET/CT in the diagnosis of PVE were 92%, 67% and 84%, respectively; positive and negative predictive values — 85% and 80%. The analysis of the odds ratio did not reveal the relationship of low inflammatory activity, the interval between surgery and PET/CT from 3 to 6 months, and long-term ABT before PET/CT with false PET/CT results (p&gt;0,05). …”
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Evaluation of the GeneXpert MTB/RIF in patients with presumptive tuberculous meningitis. by Tatiana Metcalf, Jaime Soria, Silvia M Montano, Eduardo Ticona, Carlton A Evans, Luz Huaroto, Matthew Kasper, Eric S Ramos, Nicanor Mori, Podjanee Jittamala, Kesinee Chotivanich, Irwin F Chavez, Pratap Singhasivanon, Sasithon Pukrittayakamee, Joseph R Zunt

“…Considering the 30 patients who had a clinical diagnosis of TBM: diagnostic sensitivity was 23% (7/30, 95%CI: 9.9-42%) for GeneXpert and was the same for all culture results combined; considerably greater than 7% (2/30, 95%CI: 0.82-22%) for microscopy; whereas all laboratory tests had poor negative predictive values (20-23%). Considering only the 8 patients with definite TBM: diagnostic sensitivity was 88% (7/8, 95%CI: 47-100%) for GeneXpert; 75% (6/8, 95%CI: 35-97%) for MGIT culture or LJ culture; 50% (4/8, 95%CI 16-84) for Ogawa culture and 25% (2/8, 95%CI: 3.2-65%) for microscopy. …”
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Improving chest pain risk assessment: validation of HEART, TIMI, GRACE, EDACS-ADP, and HET for MACE prediction in the emergency department by Mehdi Nasr Isfahani, Hamidreza Mohseni, Elahe Nasri Nasrabadi, Nizal Sarrafzadegan

“…Diagnostic performance of the risk scores was evaluated using receiver operating characteristic (ROC) curve analysis, including calculation of sensitivity, specificity, positive and negative predictive values, and likelihood ratios at clinically relevant cut-off thresholds. …”
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Temporal disruption in tuberculosis incidence patterns during COVID-19: a time series analysis in China by Jiarui Zhang, Zhong Sun, Qi Deng, Yidan Yu, Xingyue Dian, Juan Luo, Thilakavathy Karuppiah, Narcisse Joseph, Guozhong He

“…During the COVID-19 pandemic, there was a significant reduction in PTB cases, with actual reported cases falling below the predicted values. The disruption in PTB incidence appears to be temporary, as 2023 data indicate a gradual return to pre-pandemic trends, though the incidence rate remains slightly lower than pre-COVID levels. …”
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