Search results for "Test data generation"
showing 9 items of 9 documents
Improving the Competency of Classifiers through Data Generation
2001
This paper describes a hybrid approach in which sub-symbolic neural networks and symbolic machine learning algorithms are grouped into an ensemble of classifiers. Initially each classifier determines which portion of the data it is most competent in. The competency information is used to generated new data that are used for further training and prediction. The application of this approach in a difficult to learn domain shows an increase in the predictive power, in terms of the accuracy and level of competency of both the ensemble and the component classifiers.
Generative Adversarial Networks in Cardiology
2021
A B S T R A C T Generative Adversarial Networks (GANs) are state-of-the-art neural network models used to synthesize images and other data. GANs brought a considerable improvement to the quality of synthetic data, quickly becoming the standard for data generation tasks. In this work, we summarize the applications of GANs in the field of cardiology, including generation of realistic cardiac images, electrocardiography signals, and synthetic electronic health records. The utility of GAN-generated data is discussed with respect to research, clinical care, and academia. Moreover, we present illustrative examples of our GAN-generated cardiac magnetic resonance and echocardiography images, showin…
Assessment of computational methods for the analysis of single-cell ATAC-seq data
2019
Abstract Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans), lead to inherent data sparsity (1–10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (10–45% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level. Results We present a benchmarking framework that …
Trends in Patient Generated Data – An Initial Review
2019
In recent years, patient-centered care has gained significant momentum in healthcare and the patient is more involved as an active participant in data generation. In this state of the art review we ...
Correcting for non-ignorable missingness in smoking trends
2015
Data missing not at random (MNAR) is a major challenge in survey sampling. We propose an approach based on registry data to deal with non-ignorable missingness in health examination surveys. The approach relies on follow-up data available from administrative registers several years after the survey. For illustration we use data on smoking prevalence in Finnish National FINRISK study conducted in 1972-1997. The data consist of measured survey information including missingness indicators, register-based background information and register-based time-to-disease survival data. The parameters of missingness mechanism are estimable with these data although the original survey data are MNAR. The u…
Issues in synthetic data generation for advanced manufacturing
2017
To have any chance of application in real world, advanced manufacturing research in data analytics needs to explore and prove itself with real-world manufacturing data. Limited access to real-world data largely contrasts with the need for data of varied types and larger quantity for research. Use of virtual data is a promising approach to make up for the lack of access. This paper explores the issues, identifies challenges, and suggests requirements and desirable features in the generation of virtual data. These issues, requirements, and features can be used by researchers to build virtual data generators and gain experience that will provide data to data scientists while avoiding known or …
Event generation and statistical sampling for physics with deep generative models and a density information buffer
2021
Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events l…
Industrial Scaled Automated Structural Testing with the Evolutionary Testing Tool
2010
Evolutionary testing has been researched and promising results have been presented. However, evolutionary testing has remained predominately a research-based activity not practiced within industry. Although attempts have been made, such as Daimler's Evolutionary Structural Test (EST) prototype, until now, no such tool has been suitable for industrial adoption. The European project EvoTest (IST-33472) team has been working from 2006 till2009 to improve this situation. This paper describes the final version of the Evolutionary Testing Framework (ETF) resulting from the EvoTest project. In specific we will present the EvoTest Structural Testing tool for fully automatic structural testing that …
DATA GENERATION FOR THE ACQUISITION OF THE UNIVERSITY COURSES OF INFORMATICS AND STATISTICS IN THE HEALTH CARE SPECIALITIES
2020
The authors of the present article are investigating the influence of the data generation in the university courses of informatics and statistics (UCIS) on the acquisition of both the UCIS and other study courses in the health care specialities. First of all, the authors inquired students in order to find out their attitude to the UCIS. The inquiry results show evidence that an important role in the acquisition of UCIS has the work/study material – data. The UCIS work/study material can be associated with various branches, including health care. The data of the health care patients are of a special status. Their use is strictly regulated/limited.by legislation. The authors of the present ar…