The accuracy of diagnostic tests with binary end-points is most frequently measured by sensitivity and specificity. However, from the clinical perspective, the main purpose of a diagnostic agent is to assess the probability of a patient actually bein...
Pulmonary function tests are useful to evaluate airway obstructions and bronchial responsiveness. We aimed to determine the reference values applicable to Korean children and adolescents. In total, 5590 (2607 males, 2983 females) healthy children age...
Diagrammatic formats are useful for summarizing the processes of evaluation and comparison of forecasts in plant pathology and other disciplines where decisions about interventions for the purpose of disease management are often based on a proxy risk...
A binary diagnostic test is a medical test that is applied to an individual in order to determine the presence or the absence of a certain disease and whose result can be positive or negative. A positive result indicates the presence of the disease,...
9 February 2020
The purpose of this study was to evaluate the inspiratory and expiratory muscle strength of individuals affected by stroke and to compare it with the predicted values in the literature considering their corresponding age. Respiratory muscle strength...
Based on branch prediction, value prediction has emerged as a solution for problems caused by true data dependencies in pipelined processors. While branch predictors have binary outcomes (taken/not taken), value predictors face a challenging task as...
We present Value Prediction for Security (VPsec), a novel hardware-only framework to counter fault attacks in modern microprocessors, while preserving the performance benefits of Value Prediction (VP.) VP is an elegant and hitherto mature microarchit...
The predictive receiver operating characteristic (PROC) curve is a diagrammatic format with application in the statistical evaluation of probabilistic disease forecasts. The PROC curve differs from the more well-known receiver operating characteristi...
The natural gas quality fluctuates in complex natural gas pipeline networks, because of the influence of the pipeline transmission process, changes in the gas source, and fluctuations in customer demand in the mixing process. Based on the dynamic cha...
Pixel value ordering and prediction error expansion (PVO+PEE) is a very successful reversible data hiding (RDH) scheme. A series of studies were proposed to improve the performance of the PVO-based scheme. However, the embedding capacity of those sch...
Most machine learning (ML) models produce black box predictions that are difficult, if not impossible, to understand. In pharmaceutical research, black box predictions work against the acceptance of ML models for guiding experimental work. Hence, the...
The conversion from functional requirements (FRs) to design parameters is the foundation of product customization. However, original customer needs usually result in incomplete FRs, limited by customers’ incomprehension on the design requirements of...
The value of ecosystem services (ESV) serves as a crucial metric for assessing the cost-effectiveness of ecosystems and evaluating their economic worth. Predicting the evolution of ESV across various land uses under different scenarios is essential f...
Use of a case-control design to compare the accuracy of two binary diagnostic tests is frequent in clinical practice. This design consists of applying the two diagnostic tests to all of the individuals in a sample of those who have the disease and in...
This study introduces an empirical model designed to predict the maximum values of time-dependent data across four turbulence-related fields: hydrogen combustion in renewable energy systems, urban microclimate effects on cultural heritage, shipping e...
Remaining useful life (RUL) prediction is recently a hot spot in industrial big data analysis research. It aims at obtaining the health status of the equipment in advance and making intelligent maintenance decisions. However, values missing is a comm...
Missing values in time series data present a significant challenge, often degrading the performance of downstream tasks such as classification and forecasting. Traditional approaches address this issue by first imputing the missing values and then in...
Background/Objectives: This work introduces accuracy- and precision-ROC curves in addition to SS– and PV–ROC curves and shows a novel means of profiling biomarker characteristics for validation of optimal cutoffs in clinical diagnostics a...
Background: In the coming years, the lateral cephalogram will remain, in many cases, the preferred diagnostic tool for planning and reliably assessing the results of orthodontic treatment. The aim of this study was to compare the predictive value and...
Background: Since the outbreak of the COVID-19 pandemic, a growing number of evidence suggests that COVID-19 presents sex-dependent differences in clinical course and outcomes. Nevertheless, there is still an unmet need to stratify the risk for poor...
This study addresses the limitations of traditional coal calorific value prediction models, which primarily rely on linear regression and single-source proximate analysis data. Based on 465 Chinese coal samples and integrating proximate analysis, ult...
Completing a project on time and on budget are essential factors for the success of any project. One technique that allows predicting the final cost of a project is earned value management (EVM). In this technique, different mathematical methods for...
Anticholinergic burden (AB) is related to cognitive impairment (CI) and older complex chronic patients (OCCP) are more susceptible. Our objective was to evaluate the predictive value of ten anticholinergic scales to predict a potential CI due to anti...
As an important part of the urban ecosystem, urban green space provides a variety of ecosystem services, including climate regulation, soil conservation, carbon sink and oxygen release, and biodiversity protection. However, existing remote sensing ev...
Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), a major challenge for the swine industry, can be transmitted both vertically and horizontally. Common sample types, including processing fluid, serum, and family oral fluid, can neither det...
To investigate the value of 18F-FDG-PET/CT in predicting the occurrence of brain metastases in melanoma patients, in this retrospective study 201 consecutive patients with pathology-proven melanoma, between 2008 and 2021, were reviewed. Those who und...
This study evaluated the nutrition composition, the nutrient digestibility, and the energy value of six protein ingredients used in pet food by the difference method in six beagles within a 7 × 6 incomplete Latin square design. The results show...
The use of abnormal milk mid-infrared (MIR) spectrum strongly affects prediction quality, even if the prediction equations used are accurate. So, this record must be detected after or before the prediction process to avoid erroneous spectral extrapol...
The advantage of quantum mechanics to shift up the ability to econometrically understand extreme tail losses in financial data has become more desirable, especially in cases of Value at Risk (VaR) and Expected Shortfall (ES) predictions. Behind the n...
This article presents a new prediction model, the ordinary differential equations–memory kernel function (ODE–MKF), constructed from multiple backtracking initial values (MBIV). The model is similar to a simplified numerical model after s...
With the widespread application of artificial intelligence in real estate price prediction, model explainability has become a critical factor influencing its acceptability and trustworthiness. The Shapley value, as a classic cooperative game theory m...
Senility has been identified among the strongest risk predictors for unfavorable COVID-19-outcome. However, even in the elderly population, the clinical course of infection in individual patients remains unpredictable. Hence, there is an urgent need...
Although the prognosis of tonsillar cancer (human papillomavirus-positive oropharyngeal squamous cell carcinoma) is improving, disease control failure (distant metastasis) still occurs in some cases. We explored whether several 18F-fluorodeoxyglucose...
Background/Objectives: A perforated peptic ulcer (PPU) is a life-threatening surgical emergency, with high levels of mortality and morbidity reported in the literature. Recognizing which patients are at most risk of developing complications or losing...
Background and Objectives: Extubation success in ICU patients is crucial for reducing ventilator-associated complications, morbidity, and mortality. The Rapid Shallow Breathing Index (RSBI) is a widely used predictor for weaning from mechanical venti...
Real-valued inter-residue distance maps provide essential spatial information for understanding protein folding mechanisms and guiding downstream applications such as function annotation, drug discovery, and structural modeling. However, existing pre...
This paper addresses the cold-start problem and rare event prediction challenges in Olympic medal forecasting by proposing a predictive framework that integrates multi-granularity transfer learning with extreme value theory. The framework comprises t...
Ventilatory pump failure is a common cause of death for patients with neuromuscular diseases. The vital capacity plateau value (VCPLAT) is an important indicator to judge the status of ventilatory pump failure for patients with congenital myopathy, D...
University of Surrey’s School of Veterinary Medicine introduced an assessment called On The Spot Presentation-based Assessment (OTSPA) into the 3rd and 4th year of a 5-year veterinary degree programme. The OTSPA is designed as a low-weightage s...
We present an enhanced Extreme Value Analysis (EVA) framework designed to improve the forecasting of extremely low-production events in photovoltaic (PV) systems and to reveal the key inter-variable relationships governing performance under extreme c...
This Perspective synthesizes recent (2023–2025) progress in predicting extreme environmental values by combining empirical formulations, physics-based simulation outputs, and sensor-network data. We argue that hybrid approaches—spanning p...
This study aims to identify an equation for predicting the calorific value for heat-treated biomass using structural analysis. Different models were constructed using 129 samples of cellulose, hemicellulose, and lignin, and calorific values obtained...
This study investigates the efficacy of various genomic prediction models—Genomic Best Linear Unbiased Prediction (GBLUP), Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGB), and Multilayer Perceptron (MLP)—...
Background/Objectives: Multiple criteria are used worldwide to select hepatocellular carcinoma (HCC) patients with a low risk of recurrence for liver transplantation (LT). However, it remains unclear which criteria are best for the LT-involved stakeh...
Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs), how to implement fault-tolerant WECS control is becoming a significant iss...
Three-dimensional geological modeling combined with the information value method offers a powerful approach for predicting mineralization in complex geological settings. This study applies these techniques to the Bainiuchang Ag polymetallic deposit i...
Background and Objectives: Immunodeficiency associated with aging comorbidities increases the vulnerability of geriatric patients to sepsis. Early recognition and management of sepsis are essential in this population. This study evaluated the relatio...
The prediction of colorectal cancer (CRC) response to palliative chemotherapy (CTH) is still difficult. Patients at a higher risk of progression may benefit from more aggressive treatment. This study assessed the predictive value of prolactin (PRL) a...
Due to the global demand for dimension stones, fast and reliable evaluation tools are essential for assessing the quality of dimension stones. For this reason, this study aims to develop comprehensive tools for estimating the abrasion resistance of v...
The evaluation of landslide susceptibility is of great significance in the prevention and management of geological hazards. The accuracy of the landslide susceptibility prediction model based on machine learning is significantly higher than that of t...
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