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Siwei Yu, Jianwei Ma • Reviews of Geophysics
(2021)
Abstract Recently deep learning (DL), as a new data‐driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the...
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DOI: https://doi.org/10.1029/2021rg000742
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 A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms.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
Bang Zhu, Wenkai Cheng, Shiting Wen, Yuran Ma et al. • Scientific Reports
(2025)
Abstract The application of the $$\Phi$$ -OTDR (Phase-Optical Time Domain Reflectometry) system in real-time monitoring of power grid infrastructure has been proven effective in identifying and classifying various anomalies, such as digging...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-29691-y
Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan et al. • BMC Psychiatry
(2025)
Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...
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Open Access (DOAJ)
DOI: 10.1186/s12888-025-07196-2
salma mostafa ahmed helmy, Salsabil Amin, Abeer mahmoud, El-Sayed El-Horabty • International Journal of Intelligent Computing and Information Sciences
(2026)
The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...
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Open Access (DOAJ)
DOI: 10.21608/ijicis.2026.442636.1439
Ghenwa Chamouni, Filippo Lococo, Carolina Sassorossi, Nkunzi Atuhaire et al. • Frontiers in Public Health
(2025)
IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...
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Open Access (DOAJ)
DOI: 10.3389/fpubh.2025.1663298
Yabo Fu, Yang Lei, Tonghe Wang, Walter John Curran et al. • Physics in Medicine and Biology
(2020)
This paper presents a review of deep learning (DL)-based medical image registration methods. We summarized the latest developments and applications of DL-based registration methods in the medical field. These methods were classified into se...
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Open Access
DOI: https://doi.org/10.1088/1361-6560/ab843e
PMC: 7759388
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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DOI: https://doi.org/10.1016/j.dibe.2021.100045
Asma Cherif, Arwa Badhib, Heyfa Ammar, Suhair Alshehri et al. • Journal of King Saud University: Computer and Information Sciences
(2023)
Credit card fraud is becoming a serious and growing problem as a result of the emergence of innovative technologies and communication methods, such as contactless payment. In this article, we present an in-depth review of cutting-edge resea...
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Open Access (DOAJ)
DOI: 10.1016/j.jksuci.2022.11.008
Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia et al. • IEEE Geoscience and Remote Sensing Magazine
(2017)
Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in ...
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Open Access
DOI: https://doi.org/10.1109/mgrs.2017.2762307
Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2017)
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...
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DOI: https://doi.org/10.1109/tnnls.2017.2766168
Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics
(2020)
Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...
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DOI: https://doi.org/10.1016/j.pacs.2020.100215
PMC: 7779783
Heang‐Ping Chan, Lubomir M. Hadjiiski, Ravi K. Samala • Medical Physics
(2020)
Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then ...
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Open Access
DOI: https://doi.org/10.1002/mp.13764
PMC: 7293164
A. I. M. Schwebig, A. I. M. Schwebig, R. Tutsch • Journal of Sensors and Sensor Systems
(2020)
Ensuring the highest quality standards at competitive prices is one of the greatest challenges in the manufacture of electronic products. The identification of flaws has the uppermost priority in the field of automotive electronics, particu...
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Open Access (DOAJ)
DOI: 10.5194/jsss-9-167-2020
Dimitrios Georgiou, Sotiris Kotsiantis, Fotini Sereti • Mathematics
(2026)
Topological data analysis (TDA) has evolved into a flexible and robust paradigm for obtaining qualitative, geometry-inspired insights from high-dimensional, noisy, and complex data. Grounded in algebraic topology, geometry, statistics, and ...
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Open Access (DOAJ)
DOI: 10.3390/math14122205
Jiao Li, Xiaojuan Jing, Qin Zhang, Xiaoxiang Wang et al. • BMC Medical Informatics and Decision Making
(2025)
Abstract Background Subepithelial lesions (SELs) present significant diagnostic challenges in gastrointestinal endoscopy, particularly in differentiating malignant types, such as gastrointestinal stromal tumors (GISTs) and neuroendocrine tu...
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Open Access (DOAJ)
DOI: 10.1186/s12911-025-03147-9
Thomas Serre • Annual Review of Vision Science
(2019)
Artificial vision has often been described as one of the key remaining challenges to be solved before machines can act intelligently. Recent developments in a branch of machine learning known as deep learning have catalyzed impressive gains...
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DOI: https://doi.org/10.1146/annurev-vision-091718-014951
Shuochao Yao, Yiran Zhao, Aston Zhang, Shaohan Hu et al. • Computer
(2018)
How can the advantages of deep learning be brought to the emerging world of embedded IoT devices? The authors discuss several core challenges in embedded and mobile deep learning, as well as recent solutions demonstrating the feasibility of...
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DOI: https://doi.org/10.1109/mc.2018.2381131
Yanhui Xi, Weijie Zhang, Feng Zhou, Xin Tang et al. • Energy Reports
(2023)
Accurate fault detection and classification help to analyze fault causes and quickly restore faulty phases. Deep learning can automatically extract fault features and identify fault types from the original three-phase voltage and current si...
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Open Access (DOAJ)
DOI: 10.1016/j.egyr.2022.12.043