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Application of artificial intelligence to the electrocardiogram

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,...

OPENALEX Open Access DOI: https://doi.org/10.1093/eurheartj/ehab649 PMC: 8500024

Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Korawege N. C. Jayasena, Battur Batkhishig, Babak Nahid-Mobarakeh, Ali Emadi • IEEE Access (2025)

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predict...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3589750

An Instructional Optimization Method Based on Bidirectional Transformer and Reinforcement Learning

Ran Zhang, Xiaoping Wu, Xude Zhang, Li Xu • IEEE Access (2025)

With the rapid development of information technology, personalized education has become a key direction for improving the quality of online learning and optimizing individualized learning paths. However, accurately recommending appropriate ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3576878

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Christoph Balada, Max Bondorf, Sheraz Ahmed, Markus Zdrallek et al. • IEEE Access (2025)

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3560811

<bold>CroSSHeteroFL</bold>: Cross-Stratified Sampling Composition-Fitting to Federated Learning for Heterogeneous Clients

Vo Phuc Tinh, Hoang Hai Son, Nguyen Hoang Nam, Duc Ngoc Minh Dang et al. • IEEE Access (2024)

In the large-scale deployment of federated learning (FL) systems, the heterogeneity of clients, such as mobile phones and Internet of Things (IoT) devices with different configurations, constitutes a significant problem regarding fairness, ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3475737

AI enhanced diagnostic accuracy and workload reduction in hepatocellular carcinoma screening

Rui-Fang Lu, Chao-Yin She, Dan-Ni He, Mei-Qing Cheng et al. • npj Digital Medicine (2025)

Abstract Hepatocellular carcinoma (HCC) ultrasound screening encounters challenges related to accuracy and the workload of radiologists. This retrospective, multicenter study assessed four artificial intelligence (AI) enhanced strategies us...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-025-01892-9

Cost-Effective Design, Content Management System Implementation and Artificial Intelligence Support of Greek Government AADE, myDATA Web Service for Generic Government Infrastructure, a Complete Analysis

George Tsamis, Georgios Evangelos, Aris Papakostas, Giannis Vassiliou et al. • Algorithms (2025)

One significant digital initiative that is changing Greece’s tax environment is the myDATA platform. The platform, which is a component of the wider digital governance agenda, provides significant added value to enterprises and the tax admi...

DOAJ Open Access (DOAJ) DOI: 10.3390/a18060339

Trustworthy artificial intelligence

Scott Thiebes, Sebastian Lins, Ali Sunyaev • Electronic Markets (2020)

Abstract Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of economies and societies, but also a variety of novel ethical, legal, social, and technological challe...

OPENALEX cc-by DOI: https://doi.org/10.1007/s12525-020-00441-4

Artificial Intelligence and Deep Learning in Ophthalmology

Daniel Shu Wei Ting, Louis Robert Pasquale, Lily Peng, John Peter Campbell et al. • Springer eBooks (2018)

Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to i...

OPENALEX Open Access DOI: https://doi.org/10.1007/978-3-030-64573-1_200 PMC: 6362807

IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends

Sameer Qazi, Bilal A. Khawaja, Qazi Umar Farooq • IEEE Access (2022)

Smart agriculture techniques have recently seen widespread interest by farmers. This is driven by several factors, which include the widespread availability of economically-priced, low-powered Internet of Things (IoT) based wireless sensors...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2022.3152544

Artificial intelligence revolutionizing anesthesia management: advances and prospects in intelligent anesthesia technology

Yannan Cao, Yixin Wang, Hang Liu, Lei Wu • Frontiers in Medicine (2025)

With the development of artificial intelligence (AI), AI-related technologies are being applied in many fields of medicine. Anesthesia is now widely used in surgery, emergency resuscitation, pain treatment and other fields. However, differe...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2025.1571725

Deep nested U-structure network with frequency attention for building semantic segmentation

Khaled Moghalles, Zaid Al-Huda, Dalal AL-Alimi, Yeong Hyeon Gu et al. • Scientific Reports (2025)

Abstract The automated segmentation of buildings from remotely sensed imagery has undergone extensive research and application across various industrial domains. Despite this, several challenges persist, including incomplete internal extrac...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-13890-8

AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction

Kecheng Huang, Chujun Wu, Rongpeng Pi, Jieyu Fang • JMIR Medical Informatics (2025)

This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function...

DOAJ Open Access (DOAJ) DOI: 10.2196/73995

Enhancing underwater target detection: Fusion of spatio‐temporal incompletely‐aligned AIS and sonar information via DTW and multi‐head attention mechanism

Wenbo Zhao, Xinghua Cheng, Dezhi Wang, Xiaodan Xiong et al. • IET Radar, Sonar & Navigation (2024)

Abstract In the field of underwater target detection, the passive sonar is an important means of long‐distance target detection. The sonar detection information typically includes both surface and underwater targets, whereas it is a great c...

DOAJ Open Access (DOAJ) DOI: 10.1049/rsn2.12653

Artificial Intelligence and Surgical Decision-making

Tyler John Loftus, Patrick James Tighe, Amanda C. Filiberto, Philip Alexander Efron et al. • JAMA Surgery (2019)

Importance: Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes...

OPENALEX Open Access DOI: https://doi.org/10.1001/jamasurg.2019.4917 PMC: 7286802