Domain-specific knowledge graphs: A survey
B Abu-Salih - Journal of Network and Computer Applications, 2021 - Elsevier
Abstract Knowledge Graphs (KGs) have made a qualitative leap and effected a real
revolution in knowledge representation. This is leveraged by the underlying structure of the …
revolution in knowledge representation. This is leveraged by the underlying structure of the …
Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …
interconnected devices, allowing the use of various smart applications. The enormous …
[HTML][HTML] HKGB: an inclusive, extensible, intelligent, semi-auto-constructed knowledge graph framework for healthcare with clinicians' expertise incorporated
Health knowledge graph provides an ideal technical means to integrate heterogeneous data
resources and enhance knowledge-based services. There are many challenges for the …
resources and enhance knowledge-based services. There are many challenges for the …
[HTML][HTML] Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques
J Civit-Masot, A Bañuls-Beaterio… - Computer Methods and …, 2022 - Elsevier
Background Lung cancer has the highest mortality rate in the world, twice as high as the
second highest. On the other hand, pathologists are overworked and this is detrimental to …
second highest. On the other hand, pathologists are overworked and this is detrimental to …
Building interpretable models for business process prediction using shared and specialised attention mechanisms
Predictive process analytics, often underpinned by deep learning techniques, is a newly
emerged discipline dedicated for providing business process intelligence in modern …
emerged discipline dedicated for providing business process intelligence in modern …
Detecting cardiac pathologies via machine learning on heart-rate variability time series and related markers
In this paper we develop statistical algorithms to infer possible cardiac pathologies, based
on data collected from 24 h Holter recording over a sample of 2829 labelled patients; labels …
on data collected from 24 h Holter recording over a sample of 2829 labelled patients; labels …
Explainable ai (xai) applied in machine learning for pain modeling: A review
Pain is a complex term that describes various sensations that create discomfort in various
ways or types inside the human body. Generally, pain has consequences that range from …
ways or types inside the human body. Generally, pain has consequences that range from …
Predicting ayurveda-based constituent balancing in human body using machine learning methods
V Madaan, A Goyal - IEEE Access, 2020 - ieeexplore.ieee.org
Human Body constitution (prakriti) defines what is in harmony with human nature and what
will cause to move out of balance and experience illness. Tridosha defines the three basic …
will cause to move out of balance and experience illness. Tridosha defines the three basic …
A robust ensemble of convolutional neural networks for the detection of monkeypox disease from skin images
Monkeypox is a smallpox-like disease that was declared a global health emergency in July
2022. Because of this resemblance, it is not easy to distinguish a monkeypox rash from other …
2022. Because of this resemblance, it is not easy to distinguish a monkeypox rash from other …
[HTML][HTML] Intelligent personal health monitoring and guidance using long short-term memory
S Velliangiri, V Anbarasu… - Journal of Mobile …, 2022 - journals.riverpublishers.com
Rapid improvements in information technology have made everything in this world
contemporary. The mobile phone plays a vital role in the day to day activities. Many mobile …
contemporary. The mobile phone plays a vital role in the day to day activities. Many mobile …