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Academic Articles & Research Papers
Showing 20 of 142 academic articles
Lin Bing, Tan Xiao, He Kai, Wu Huaming • Tongxin xuebao
(2026)
Satellite edge computing faces a trade-off between privacy protection and system overhead, strict task-dependency constraints, and the limited ability of conventional algorithms to capture complex dependency topologies in digital twin task ...
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Open Access (DOAJ)
Travers H. Ching, Daniel Scott Himmelstein, Brett K. Beaulieu‐Jones, Alexandr A. Kalinin et al. • Journal of The Royal Society Interface
(2018)
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and m...
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DOI: https://doi.org/10.1098/rsif.2017.0387
PMC: 5938574
Jiasi Chen, Xukan Ran • Proceedings of the IEEE
(2019)
Deep learning is currently widely used in a variety of applications, including computer vision and natural language processing. End devices, such as smartphones and Internet-of-Things sensors, are generating data that need to be analyzed in...
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DOI: https://doi.org/10.1109/jproc.2019.2921977
Binghui Wang, Neil Zhenqiang Gong • IEEE Symposium on Security and Privacy (S&P)
(2018)
Hyperparameters are critical in machine learning, as different hyperparameters often result in models with significantly different performance. Hyperparameters may be deemed confidential because of their commercial value and the confidentia...
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Open Access
DOI: https://doi.org/10.1109/sp.2018.00038
Yernazar Bolat, Iain Murray, Yifei Ren, Nasim Ferdosian • Sensors
(2025)
The growing adoption of IoT applications has led to increased use of low-power microcontroller units (MCUs) for energy-efficient, local data processing. However, deploying deep neural networks (DNNs) on these constrained devices is challeng...
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Open Access (DOAJ)
DOI: 10.3390/s25154595
Hafsa Habehh, Suril Gohel • Current Genomics
(2021)
Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, among...
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Open Access
DOI: https://doi.org/10.2174/1389202922666210705124359
PMC: 8822225
Ling Huang, Anthony D. Joseph, Blaine A. Nelson, Benjamin I. P. Rubinstein et al. • ACM Workshop on Artificial Intelligence and Security (AISec)
(2011)
In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...
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DOI: https://doi.org/10.1145/2046684.2046692
Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining
(2021)
Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...
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Open Access (DOAJ)
DOI: 10.1186/s13040-021-00271-w
Ethem Alpaydın • The MIT Press eBooks
(2021)
A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars. Today, machine learning underlies a range of applications we use every day, from product ...
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Open Access
DOI: https://doi.org/10.7551/mitpress/13811.001.0001
Eileen Donahoe, Megan MacDuffee Metzger • Journal of democracy
(2019)
Rapid adoption of artificial intelligence (AI) technologies and increased reliance upon AI by both governments and the private sector have led to rising concern about potential negative implications for human dignity, democratic accountabil...
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DOI: https://doi.org/10.1353/jod.2019.0029
Elena Guerini-Rocco, Chiara Frascarelli, Joana Sorino, Francesca Maria Porta et al. • Applied Sciences
(2026)
Designing an optimal digital pathology workspace is essential to ensure diagnostic accuracy and safeguard the long-term well-being of pathologists. While digital pathology improves reproducibility, facilitates multidisciplinary collaboratio...
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Open Access (DOAJ)
DOI: 10.3390/app16126021
Isha Duggal, Tulika Tripathi • Journal of Oral Biology and Craniofacial Research
(2024)
In the current technological era, dental practitioners are faced with various ethical challenges, highlighting the importance of bioethics in this healthcare discipline. The rise of artificial intelligence has recently sparked a debate rega...
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Open Access (DOAJ)
DOI: 10.1016/j.jobcr.2024.04.003
James Curzon, Tracy Ann Kosa, Rajen Akalu, Khalil El‐Khatib • IEEE Transactions on Artificial Intelligence
(2021)
Artificial intelligence is a rapidly developing field of research with many practical applications. Congruent to advances in technologies that enable big data, deep learning, and neural networks to train, learn, and predict, artificial inte...
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DOI: https://doi.org/10.1109/tai.2021.3088084
Muneesh Joshi, Kuhu Sharma • Archives of Medicine and Health Sciences
(2026)
Periodontitis is a chronic inflammatory disease that affects the tissues supporting teeth and represents a significant global health issue. Traditional diagnostic and treatment methods often use a broad approach and fall short due to the co...
DOAJ
Open Access (DOAJ)
DOI: 10.4103/amhs.amhs_191_25
Iván Claudio Suazo Galdames • Revista Cubana de Estomatología
(2024)
Introduction: The introduction of artificial intelligence-driven applications is revolutionizing dentomaxillofacial imaging.
Objectives: To describe the current status of artificial intelligence applications in dentomaxillofacial diagnosti...
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Open Access (DOAJ)
Heike Felzmann, Eduard Fosch‐Villaronga, Christoph Lutz, Aurelia Tamò‐Larrieux • Science and Engineering Ethics
(2020)
In this article, we develop the concept of Transparency by Design that serves as practical guidance in helping promote the beneficial functions of transparency while mitigating its challenges in automated-decision making (ADM) environments....
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DOI: https://doi.org/10.1007/s11948-020-00276-4
PMC: 7755865
Zachi Itzhak Attia, David Harmon, Elijah Raphael Behr, Paul A. Friedman • European Heart Journal
(2021)
Artificial intelligence (AI) has given the electrocardiogram (ECG) and clinicians reading them super-human diagnostic abilities. Trained without hard-coded rules by finding often subclinical patterns in huge datasets, AI transforms the ECG,...
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Open Access
DOI: https://doi.org/10.1093/eurheartj/ehab649
PMC: 8500024
Chen Xinyu, Hui Tianfang, Li Yanlin, Yang Haoyuan • ITM Web of Conferences
(2025)
As artificial intelligence (AI) is increasingly integrated into society, people are relying on it more and more, and higher requirements are put forward for the safety and ethical standards of AI. This article explores the development of ar...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/itmconf/20257004031
Thomas H. Davenport, Abhijit Guha, Dhruv Grewal, Timna Breßgott • Journal of the Academy of Marketing Science
(2019)
Abstract In the future, artificial intelligence (AI) is likely to substantially change both marketing strategies and customer behaviors. Building from not only extant research but also extensive interactions with practice, the authors propo...
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DOI: https://doi.org/10.1007/s11747-019-00696-0
Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb B • Innovation Policy and the Economy
(2018)
Recent progress in artificial intelligence (AI)—a general purpose technology affecting many industries—has been focused on advances in machine learning, which we recast as a quality-adjusted drop in the price of prediction. How will this sh...
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DOI: https://doi.org/10.1086/699935