model-based

Idiopathic pulmonary fibrosis (IPF) is a life-threatening interstitial lung disease. Identifying biomarkers for early diagnosis is of great clinical importance. The epididymis protein 4 (HE4) is important in the process of inflammation and fibrosis in the epididymis. Its prognostic value in IPF, however, has not been studied. The mRNA and protein levels of HE4 were used to determine the prognostic value in different patient cohorts. In this study, prognostic nomograms were generated based on the results of the cox regression analysis...

This study proposes a novel robust optimization approach for an integrated water supply system, wherein the decision-makers attempt to improve failure safety of system under various uncertainty strategies. To cope with uncertainty, the ellipsoid uncertainty set is assumed to evaluate the best feasible solution in the direction of water supply under various strategies. We assessed the case of Hamoun watershed, a water-stressed watershed in southeastern of Iran, to evaluate the developed robust optimization model...

Accurate and efficient motion estimation is a crucial component of real-time ultrasound elastography (USE). However, obtaining radiofrequency ultrasound (RF) data in clinical practice can be challenging. In contrast, although B-mode (BM) data is readily available, elastographic data derived from BM data results in sub-optimal elastographic images. Furthermore, existing conventional ultrasound devices (e.g., portable devices) cannot provide elastography modes, which has become a significant obstacle to the widespread use of traditional ultrasound devices...

Wood ashes can be used, e.g., as soil fertilizer or in construction materials; however, it is important to ensure that such use will not cause spreading of heavy metals and subsequent harm to the environment. Wood fly ashes (WFAs) generally have higher concentrations of heavy metals than wood bottom ashes. This paper focuses on the leaching of heavy metals from WFA, specifically identifying WFA characteristics that influence the leaching and changes in leaching caused by hydration and carbonation in ambient air...

Is the radiomic approach, utilizing diffusion-weighted imaging (DWI), capable of predicting the various pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC)? Furthermore, which model demonstrates superior performance among the diverse algorithms currently available? The objective of our study is to develop DWI radiomic models based on different machine learning algorithms and identify the optimal prediction model. We undertook a retrospective analysis of the DWI data of 77 patients with IMCC confirmed by pathological testing...

We use data produced by industrial wood grading machines to train a machine learning model for predicting strength-related properties of wood lamellae from colour images of their surfaces. The focus was on samples of Norway spruce ( Picea abies ) wood, which display visible fibre pattern formations on their surfaces. We used a pre-trained machine learning model based on the residual network ResNet50 that we trained with over 15 000 high-definition images labelled with the indicating properties measured by the grading machine...

Evaluating the rehabilitation status of individuals with serious mental illnesses (SMI) necessitates a comprehensive analysis of multimodal data, including unstructured text records and structured diagnostic data. However, progress in the effective assessment of rehabilitation status remains limited. Our study develops a deep learning model integrating Bidirectional Encoder Representations from Transformers (BERT) and TabNet through a late fusion strategy to enhance rehabilitation prediction, including referral risk, dangerous behaviors, self-awareness, and medication adherence, in patients with SMI...

The association between parental burnout and perfectionism, and whether and to what extent it is mediated by self-compassion, in case of mothers of children with Specific Learning Disorder (SLD) were rarely investigated in the related literature. To fill the gap felt, the present study aimed at providing a model for self-compassion, parental burnout, and perfectionism. The participants were 305 mothers of children with SLD, from Hamedan province, Iran, who had been referred to the relevant treatment centers between 2020 and 2021...

BACKGROUND: Preterm infants have imperfect neurological development, uncoordinated sucking-swallowing-breathing, which makes it difficult to realize effective oral feeding after birth. How to help preterm infants achieve complete oral feeding as soon as possible has become an important issue in the management of preterm infants. Non-nutritive sucking (NNS), as a useful oral stimulation, can improve the effect of oral feeding in preterm infants. This review aimed to explore the effect of NNS on oral feeding progression through a meta-analysis...

Arid zone grassland is a crucial component of terrestrial ecosystems and plays a significant role in ecosystem protection and soil erosion prevention. However, accurately mapping grassland spatial information in arid zones presents a great challenge. The accuracy of remote sensing grassland mapping in arid zones is affected by spectral variability caused by the highly diverse landscapes. In this study, we explored the potential of a rectangular tile classification model, constructed using the random forest algorithm and integrated images from Sentinel-1A (synthetic aperture radar imagery) and Sentinel-2 (optical imagery), to enhance the accuracy of grassland mapping in the semiarid to arid regions of Ordos, China...

CONTEXT: Gestational diabetes mellitus (GDM) is a pregnancy complicated disease that poses a risk to maternal and infant health. However, the etiology of the disease has been not yet elucidated. OBJECTIVE: To detect the genetic susceptibility and construct a nomogram model with significantly associated polymorphisms and key clinical indicators for early prediction of gestational diabetes mellitus (GDM). METHODS: 11 functional single nucleotide polymorphisms (SNPs) screened by genome-wide association study (GWAS) were genotyped in 554 GDM cases and 641 healthy controls...

Hydrate-based CO2 storage in the ocean is considered a potential method for mitigating the greenhouse effect. Numerous studies demonstrated that NaCl exhibited the dual effects of promotion and inhibition in the nucleation and growth processes of CO2 hydrate, whose mechanisms remain unclear. In this study, the effects of NaCl at various concentrations on the CO2 hydrate growth and crystal are investigated. The independent gradient model based on Hirshfeld partition, electrostatic potential, and binding energy is conducted to study the interaction between ions and water molecules...

Sample surveys are extensively used to provide reliable direct estimates for large areas or domains with enough sample sizes at national and regional levels. However, zones are unplanned domains by the Demographic and Health Survey (DHS) program and need more sample sizes to produce direct survey estimates with adequate precision. Conducting surveys in small areas (like zones) is too expensive and time-consuming, making it unfeasible for developing countries like Ethiopia. Therefore, this study aims to use the Hierarchical Bayes (HB) Small Area Estimation (SAE) model to estimate the Community-Based Health Insurance (CBHI) coverage at the zone levels in Ethiopia...

INTRODUCTION: The National Eye Institute Visual Function Questionnaire (NEI VFQ) is a common patient-reported outcome measure (PROM) in uveitis trials. Its psychometric properties using state-of-the-art scoring based on Rasch models, a latent trait model that improves accuracy of PROMs assessment, has not yet been investigated. METHODS: The study participants were recruited online from uveitis patient organizations, where individuals self-reported their uveitis diagnosis and visual acuity level...

Mobile apps for healthcare (mHealth apps for short) have been increasingly adapted to help users manage their health or to get healthcare services. User feedback analysis is a pertinent method that can be used to improve the quality of mHealth apps. The objective of this paper is to use supervised machine learning algorithms to evaluate the quality of mHealth apps according to the ISO/IEC 25010 quality model based on user feedback. For this purpose, a total of 1682 user reviews have been collected from 86 mHealth apps provided by Google Play Store...

Built upon the shoulders of graph theory, the field of complex networks has become a central tool for studying real systems across various fields of research. Represented as graphs, different systems can be studied using the same analysis methods, which allows for their comparison. Here, we challenge the widespread idea that graph theory is a universal analysis tool, uniformly applicable to any kind of network data. Instead, we show that many classical graph metrics-including degree, clustering coefficient, and geodesic distance-arise from a common hidden propagation model: the discrete cascade...

Background: Oral and inhalation-based cannabidiol (CBD) administration has been clinically evaluated for various therapeutic indications, alongside widespread off-label use. However, the long-term exposure kinetics and varied bioavailability have not been fully characterized. Methods: Human CBD plasma concentration-time profiles from six studies evaluating the oral administration of Epidiolex® and three studies evaluating inhalation-based delivery were obtained. A four-compartment pharmacokinetic (PK) model with Weibull-based oral absorption kinetics was employed to describe the long-term PKs of CBD...

BACKGROUND: A major impact of the invasive Myocastor coypus in the introduction range is the collapse of riverbanks and nearby infrastructure, such as railway lines, due to the species' burrowing activities. As the ubiquitous implementation of preventive measures along watercourses is unfeasible, identifying susceptible areas is key to guide targeted management actions. This study used species-habitat models to (i) identify the local environmental features of the railway line/watercourse intersections (RLWIs) that make them particularly susceptible to coypu damage, and (ii) predict species occurrence probability in a wide lowland-hilly area of northern Italy (Lombardy) to identify priority areas for monitoring...

BACKGROUND: Computed tomography (CT) radiomics combined with deep transfer learning was used to identify cholesterol and adenomatous gallbladder polyps that have not been well evaluated before surgery. PURPOSE: To investigate the potential of various machine learning models, incorporating radiomics and deep transfer learning, in predicting the nature of cholesterol and adenomatous gallbladder polyps. MATERIAL AND METHODS: A retrospective analysis was conducted on clinical and imaging data from 100 patients with cholesterol or adenomatous polyps confirmed by surgery and pathology at our hospital between September 2015 and February 2023...

OBJECTIVES: Lymphovascular invasion serves as a crucial prognostic indicator in invasive breast cancer, influencing treatment decisions. We aimed to develop a machine learning model utilizing optimal volumes of interest extracted from multisequence magnetic resonance images to predict lymphovascular invasion in patients with invasive breast cancer. MATERIALS AND METHODS: This study comprised 191 patients postoperatively diagnosed with invasive breast cancer through multi-sequence magnetic resonance imaging...