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Article
Open AccessFIT calculator: a multi-risk prediction framework for medical outcomes using cardiorespiratory fitness data
Accurately predicting patients' risk for specific medical outcomes is paramount for effective healthcare management and personalized medicine. While a substantial body of literature addresses the prediction of...
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Article
Open AccessAn interpretable semi-supervised framework for patch-based classification of breast cancer
Develo** effective invasive Ductal Carcinoma (IDC) detection methods remains a challenging problem for breast cancer diagnosis. Recently, there has been notable success in utilizing deep neural networks in v...
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Article
Open AccessExploiting time series of Sentinel-1 and Sentinel-2 to detect grassland mowing events using deep learning with reject region
Governments pay agencies to control the activities of farmers who receive governmental support. Field visits are costly and highly time-consuming; hence remote sensing is widely used for monitoring farmers’ ac...
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Article
Open AccessDLBench: a comprehensive experimental evaluation of deep learning frameworks
Deep Learning (DL) has achieved remarkable progress over the last decade on various tasks such as image recognition, speech recognition, and natural language processing. In general, three main crucial aspects ...
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Article
SDDM: an interpretable statistical concept drift detection method for data streams
Machine learning models assume that data is drawn from a stationary distribution. However, in practice, challenges are imposed on models that need to make sense of fast-evolving data streams, where the content...
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Book and Living Reference Work (Continuously updated edition)
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Chapter and Conference Paper
On Teaching Web Stream Processing
Web Stream Processing (WSP) is a field that studies how to identify, access, represent and process flows of data using Web technologies. One of the barriers that currently limits the adoption of WSP is the pa...
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Chapter
Introduction
There is no doubt that we are living the era of big data where we are witnessing radical expansion and integration of digital devices, networking, data storage, and computation systems. In practice, data gener...
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Chapter
Large-Scale Processing Systems of Structured Data
In practice, it has been acknowledged that Hadoop framework is not an adequate choice for supporting interactive queries which aim of achieving a response time of milliseconds or few seconds. In addition, many...
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Chapter
Large-Scale Stream Processing Systems
In every second of every day, we are generating massive amounts of data. In general, stream computing is a new paradigm which has been necessitated by new data-generating scenarios, such as the ubiquity of mob...
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Chapter
Conclusions and Outlook
Big data analytics is currently representing a revolution that cannot be missed. It is significantly transforming and changing various aspects in our modern life including the way we live, socialize, think, wo...
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Chapter and Conference Paper
A First Step Towards a Streaming Linked Data Life-Cycle
Alongside with the ongoing initiative of FAIR data management, the problem of handling Streaming Linked Data (SLD) is relevant as never before. The Web is changing to tame Data Velocity and fulfill the needs of a...
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Chapter and Conference Paper
Automated Machine Learning: Techniques and Frameworks
Nowadays, machine learning techniques and algorithms are employed in almost every application domain (e.g., financial applications, advertising, recommendation systems, user behavior analytics). In practice, t...
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Chapter
General-Purpose Big Data Processing Systems
In general, the discovery process often employs analytics techniques from a variety of genres such as time-series analysis, text analytics, statistics, and machine learning. Moreover, the process might involve...
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Chapter
Large-Scale Graph Processing Systems
Graphs are recognized as a general, natural, and flexible data-abstraction that can model complex relationships, interactions, and interdependencies between objects. Graphs have been widely used to represent d...
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Chapter
Large-Scale Machine/Deep Learning Frameworks
With the wide availability of data and increasing capacity of computing resources, machine learning and deep learning techniques have become very popular techniques on harnessing the power of data by achieving...
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Article
Big SQL systems: an experimental evaluation
Recently, Big Data systems have been gaining increasing popularity on handling the massive amounts of data that are continuously generated in our digital world. While the Hadoop framework has pioneered the are...
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Article
Open AccessOn the interpretability of machine learning-based model for predicting hypertension
Although complex machine learning models are commonly outperforming the traditional simple interpretable models, clinicians find it hard to understand and trust these complex models due to the lack of intuitio...
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Article
Correction to: Runtime self-monitoring approach of business process compliance in cloud environments
The original version of this article unfortunately contained a mistake in the acknowledgement statement.
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Reference Work Entry In depth
Native Distributed RDF Systems
