Results 51 to 60 of about 267,347 (270)

Deep Learning Cluster Structures for Management Decisions: The Digital CEO

Sensors, 2018
This paper presents a Deep Learning (DL) Cluster Structure for Management Decisions that emulates the way the brain learns and makes choices by combining different learning algorithms.
Will Serrano
doaj   +1 more source

Maximizing energy efficiency in wireless sensor networks for data transmission: A Deep Learning-Based Grouping Model approach

Alexandria Engineering Journal, 2023
Wireless Sensor Networks (WSNs) are widely studied for their data collection and monitoring capabilities across diverse applications. However, the limited energy resources of sensor nodes present a significant challenge in extending the network's ...
I. Surenther, K.P. Sridhar, Michaelraj Kingston Roberts   +2 more
doaj   +1 more source

Large‐scale bidirectional arrayed genetic screens identify OXR1 and EMC4 as modifiers of αSynuclein aggregation

FEBS Open Bio, EarlyView.
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane, Lea Nikolić, Lorenzo Maraio, Thomas Goiran, Nathan Karpilovsky, Stefano Sellitto, Vangelis Bouris, Jiang‐An Yin, Ronald Melki, Edward A Fon, Adriano Aguzzi, Elena De Cecco   +11 more
wiley   +1 more source

Study of Deep Learning in Medical Education: Opportunities, Achievements and Future Challenges [PDF]

Journal of Advances in Medical Education and Professionalism
Introduction: In this era of progress, interest has developed regarding advancing deep learning (DL) in medicine. However, there has been reluctance to use deep learning, particularly among medical educators.
HOSSEIN MORADIMOKHLES, GWO-JEN HWANG, HOSSEIN ZANGENEH, MARYAM POURJAMSHIDI, AMIR HOSSEIN AMOOEIRAZANI   +4 more
doaj   +1 more source

Artificial Intelligence in Optical Communications: From Machine Learning to Deep Learning

Frontiers in Communications and Networks, 2021
Techniques from artificial intelligence have been widely applied in optical communication and networks, evolving from early machine learning (ML) to the recent deep learning (DL). This paper focuses on state-of-the-art DL algorithms and aims to highlight
Danshi Wang, Min Zhang
doaj   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

A survey of malware detection using deep learning

Machine Learning with Applications
The problem of malicious software (malware) detection and classification is a complex task, and there is no perfect approach. There is still a lot of work to be done. Unlike most other research areas, standard benchmarks are difficult to find for malware
Ahmed Bensaoud, Jugal Kalita, Mahmoud Bensaoud   +2 more
doaj   +1 more source

MR image reconstruction using deep density priors

, 2018
Algorithms for Magnetic Resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data.
Baumgartner, Christian F., Konukoglu, Ender, Luechinger, Roger, Pruessmann, Klaas P., Tezcan, Kerem C.   +4 more
core   +1 more source

A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento, Daniela F. Santos, Tuane C. R. G. Vieira, Tiago F. Outeiro   +3 more
wiley   +1 more source

DL-Scale: Deep Learning for model upgrading in topology optimization

Procedia Manufacturing, 2020
Abstract Topology optimization is used for defining the optimal arrangement of material within a specific domain with respect to transferring specific loads to predetermined supports in the best possible way. Deep learning techniques have achieved significant results in computer vision [1], natural language processing [1], big-data management [2 ...
Nikos Ath. Kallioras, Nikos D. Lagaros
openaire   +1 more source