Search results for "prediction model"
showing 10 items of 17 documents
Machine Learning-Based Approach Highlights the Use of a Genomic Variant Profile for Precision Medicine in Ovarian Failure
2021
Ovarian failure (OF) is a common cause of infertility usually diagnosed as idiopathic, with genetic causes accounting for 10–25% of cases. Whole-exome sequencing (WES) may enable identifying contributing genes and variant profiles to stratify the population into subtypes of OF. This study sought to identify a blood-based gene variant profile using accumulation of rare variants to promote precision medicine in fertility preservation programs. A case–control (n = 118, n = 32, respectively) WES study was performed in which only non-synonymous rare variants <
Hydrothermal Aging of an Epoxy Resin Filled with Carbon Nanofillers
2020
The effects of temperature and moisture on flexural and thermomechanical properties of neat and filled epoxy with both multiwall carbon nanotubes (CNT), carbon nanofibers (CNF), and their hybrid components were investigated. Two regimes of environmental aging were applied: Water absorption at 70 °
Evaluation of appendicitis risk prediction models in adults with suspected appendicitis.
2019
Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (pro…
Recent advances in machine learning for maximal oxygen uptake (VO2 max) prediction : A review
2022
Maximal oxygen uptake (VO2 max) is the maximum amount of oxygen attainable by a person during exercise. VO2 max is used in different domains including sports and medical sciences and is usually measured during an incremental treadmill or cycle ergometer test. The drawback of directly measuring VO2 max using the maximal test is that it is expensive and requires a fixed and controlled protocol. During the last decade, various machine learning models have been developed for VO2 max prediction and numerous studies have attempted to predict VO2 max using data from submaximal and non-exercise tests. This article gives an overview of the machine learning models developed over the past five years (…
BRCA1/2 variants of unknown significance in hereditary breast and ovarian cancer (HBOC) syndrome: Looking for the hidden meaning
2021
Hereditary breast and ovarian cancer syndrome is caused by germline mutations in BRCA1/2 genes. These genes are very large and their mutations are heterogeneous and scattered throughout the coding sequence. In addition to the above-mentioned mutations, variants of uncertain/unknown significance (VUSs) have been identified in BRCA genes, which make more difficult the clinical management of the patient and risk assessment. In the last decades, several laboratories have developed different databases that contain more than 2000 variants for the two genes and integrated strategies which include multifactorial prediction models based on direct and indirect genetic evidence, to classify the VUSs a…
Preoperative CT-Based Deep Learning Model for Predicting Risk Stratification in Patients With Gastrointestinal Stromal Tumors.
2021
ObjectiveTo develop and evaluate a deep learning model (DLM) for predicting the risk stratification of gastrointestinal stromal tumors (GISTs).MethodsPreoperative contrast-enhanced CT images of 733 patients with GISTs were retrospectively obtained from two centers between January 2011 and June 2020. The datasets were split into training (n = 241), testing (n = 104), and external validation cohorts (n = 388). A DLM for predicting the risk stratification of GISTs was developed using a convolutional neural network and evaluated in the testing and external validation cohorts. The performance of the DLM was compared with that of radiomics model by using the area under the receiver operating char…
Prediction of type 2 diabetes mellitus based on nutrition data
2021
Abstract Numerous predictive models for the risk of type 2 diabetes mellitus (T2DM) exist, but a minority of them has implemented nutrition data so far, even though the significant effect of nutrition on the pathogenesis, prevention and management of T2DM has been established. Thus, in the present study, we aimed to build a predictive model for the risk of T2DM that incorporates nutrition data and calculates its predictive performance. We analysed cross-sectional data from 1591 individuals from the population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013–14) and used a bootstrap enhanced elastic net penalised multivariate regression method in order to bu…
An NTC zone compliant knock onset prediction model for spark ignition engines
2015
Abstract Pollutant emissions reduction and energy saving policies increased the production of Spark Ignition (SI) engines operated with gaseous fuels. Natural Gas (NG) and Liquefied Petroleum Gas (LPG), thanks to their low cost and low environmental impact represent the best alternative. Bi-fuel engines, which may run either with gasoline or with gas (NG or LPG), widely spread in many countries thanks to their versatility, high efficiency and low pollutant emissions: gas fueled vehicles, as example, are allowed to run in many limited traffic zones. In the last years, supercharged SI engines fueled with either gasoline or gaseous fuel, spread in the market. Thermodynamic simulations, widely …
Simplified Procedure for Evaluating the Effects of Creep and Shrinkage on Prestressed Concrete Girder Bridges and the Application of European and Nor…
2013
The effects of time-dependent phenomena on concrete prestressed girder bridges are investigated. The study concerns the case of bridges built directly in their final configuration and that of bridges built by a sequence of stages in which geometry, restraints, and loads vary until the final configuration is achieved. An analytical approach based on the principles of aging linear viscoelasticity and the age-adjusted effective modulus method is followed. The paper has two aims: the first is to provide an efficient and simplified tool for the evaluation of the structural response in the early stages of design; the second is to compare the results of the analyses on actual cases of bridges when…
COMPLEX ANALYSIS OF COMPANY BANKRUPTCY FORECASTING: THEORETICAL INSIGHT
2018
In modern conditions for dynamic and competitive businesses, more and more companies face financial problems and eventually go bankrupt. A noteworthy trend: not only new companies that have not yet managed to establish themselves in the market go bankrupt but also large companies operating for years and maintaining good traditions. Bankruptcies of companies cause many problems not only for the companies themselves but also for the state and many members of society. Thus, it is crucial to evaluate the financial state of a company and its activity results as accurately and early as possible when forecasting the possibility of a bankruptcy. The paper recommends a complex analysis methodology f…