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Dulani Meedeniya • Chapman & Hall/CRC eBooks
(2023)
This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....
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public-domain
DOI: https://doi.org/10.1201/9781003390824
Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charų C. Aggarwal et al. • ACM Computing Surveys
(2024)
Time series anomaly detection is important for a wide range of research fields and applications, including financial markets, economics, earth sciences, manufacturing, and healthcare. The presence of anomalies can indicate novel or unexpect...
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cc-by
DOI: https://doi.org/10.1145/3691338
Zhihua Xie BS, Jinfeng Liu PhD, Lixia Hou MS, Haoran Feng MS et al. • Technology in Cancer Research & Treatment
(2026)
Introduction Leukemia is one of the most prevalent cancers in children. The use of total marrow and lymphoid irradiation (TMLI) via helical tomotherapy (TOMO) as a conditioning regimen prior to bone marrow transplant (BMT) has been widely a...
DOAJ
Open Access (DOAJ)
DOI: 10.1177/15330338261426261
Mecit Kantarcı, Volkan Kızılgöz, Ramazan Terzi, Ahmet Enes Kılıç et al. • Diagnostic and Interventional Radiology
(2025)
PURPOSE: This study aimed to evaluate the effectiveness of artificial intelligence (AI) in diagnosing focal nodular hyperplasia (FNH) of the liver using magnetic resonance imaging (MRI) and compare its performance with that of radiologists....
DOAJ
Open Access (DOAJ)
DOI: 10.4274/dir.2025.243095
Z. Karami • Fanāvarī-i āmūzish
(2023)
Background and Objectives: In order to solve the problem of education in complex and unstructured domains, Spiro and his colleagues proposed the theory of cognitive flexibility, in which they advocated multiple forms of pedagogical models, ...
DOAJ
Open Access (DOAJ)
DOI: 10.22061/tej.2023.9686.2885
Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar et al. • Technologies
(2023)
Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/technologies11020055
Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences
(2025)
In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15031552
P. V. Chandrika, Sandeep Kelkar • Advances in medical diagnosis, treatment, and care (AMDTC) book series
(2024)
This chapter deals with the basic understanding of the deep learning model. It starts with a view of artificial intelligence, machine learning, and deep learning. It also represents how these three concepts are related to each other. The en...
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DOI: https://doi.org/10.4018/979-8-3693-1281-0.ch001
Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad-Khasmakhi et al. • ACM Computing Surveys
(2021)
Deep learning--based models have surpassed classical machine learning--based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this art...
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Open Access
DOI: https://doi.org/10.1145/3439726
Misha Denil, Babak Shakibi, Laurent Dinh, Marc’Aurelio Ranzato et al. • arXiv (Cornell University)
(2013)
We demonstrate that there is significant redundancy in the parameterization of several deep learning models. Given only a few weight values for each feature it is possible to accurately predict the remaining values. Moreover, we show that n...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1306.0543
Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics
(2018)
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...
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DOI: https://doi.org/10.1093/bfgp/ely030
Shiqi Feng, Xuquan Wang, Xiong Dun, Zhanshan Wang et al. • IEEE Photonics Journal
(2025)
Encoded computational hyperspectral cameras, propelled by advances in compressed sensing theory, making both miniaturization and real-time hyperspectral imaging feasible. Spectral-encoded or spatial-encoded hyperspectral imaging strategy ha...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JPHOT.2025.3624799
Kalab Yigermal Gete, Asnakew Achaw Ayele • BMC Neurology
(2025)
Abstract Background Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection. Objectives To estimate the diagnostic accu...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12883-025-04528-3
Jun Cheng, Thi Yen Duong Nguyen, Kamil J. Cygan, Muhammed Hasan Çelik et al. • Genome Biology
(2019)
Abstract Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI5 exon skipping predic...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13059-019-1653-z
Ardian Kelmendi, George Pappas • Algorithms
(2025)
The automotive industry increasingly relies on 3D modeling technologies to design and manufacture vehicle components with high precision. One critical challenge is optimizing the placement of latches that secure the dashboard side paneling,...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/a18090553
R. S. Basavanna, Ishaan Adhaulia, N. M. Dhanyakumar, Jyoti Joshi • Contemporary Clinical Dentistry
(2025)
Background:
The integration of artificial intelligence in dentistry has seen remarkable advancements, especially in diagnostic imaging. This study evaluates and compares the accuracy of deep learning models with that of dental postgraduate ...
DOAJ
Open Access (DOAJ)
DOI: 10.4103/ccd.ccd_274_24
Ahmad Y. Javaid, Quamar Niyaz, Weiqing Sun, Mansoor Alam • International Conference on Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS)
(2016)
A Network Intrusion Detection System (NIDS) helps system administrators to detect network security breaches in their organizations. However, many challenges arise while developing a flexible and efficient NIDS for unforeseen and unpredictab...
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DOI: https://doi.org/10.4108/eai.3-12-2015.2262516
Yayin Xu, Ying Zhou, Przemysław Sekuła, Lieyun Ding • Developments in the Built Environment
(2021)
The development of artificial intelligence technology is currently bringing about new opportunities in construction. Machine learning is a major area of interest within the field of artificial intelligence, playing a pivotal role in the pro...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.dibe.2021.100045
Haohan Wang, Bhiksha Raj • arXiv (Cornell University)
(2017)
This paper is a review of the evolutionary history of deep learning models. It covers from the genesis of neural networks when associationism modeling of the brain is studied, to the models that dominate the last decade of research in deep ...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1702.07800
Bethany Lusch, J. Nathan Kutz, Steven L. Brunton • Nature Communications
(2018)
Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear has the potential to enable nonlinear prediction, estimation, and control using linear theory. The Koopman operator is a leading data-driven e...
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DOI: https://doi.org/10.1038/s41467-018-07210-0
PMC: 6251871