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Artificial intelligence in reproductive medicine

Renjie Wang, Wei Dong Pan, Lei Jin, Yuehan Li et al. • Reproduction (2019)

Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availabilit...

OPENALEX cc-by DOI: https://doi.org/10.1530/rep-18-0523 PMC: 6733338

Artificial Intelligence in Meta-optics

Mu Ku Chen, Xiaoyuan Liu, Yanni Sun, Din Ping Tsai • Chemical Reviews (2022)

Recent years have witnessed promising artificial intelligence (AI) applications in many disciplines, including optics, engineering, medicine, economics, and education. In particular, the synergy of AI and meta-optics has greatly benefited b...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1021/acs.chemrev.2c00012 PMC: 9562283

Towards Transparency by Design for Artificial Intelligence

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....

OPENALEX cc-by DOI: https://doi.org/10.1007/s11948-020-00276-4 PMC: 7755865

IEEE Access Special Section Editorial: 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility

Ke Guan, Markus Rupp, Thomas Kurner, Cesar Briso et al. • IEEE Access (2020)

Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050, more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3037635

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Song Zeng, Xin-Lu Wang, Hua Yang • Military Medical Research (2024)

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40779-024-00580-1

Artificial intelligence in glaucoma

Chengjie Zheng, Thomas V. Johnson, Aakriti Garg Shukla, Michael Vincent Boland • Current Opinion in Ophthalmology (2018)

PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making, and artificial intelligence methods have recently demonstrated significant advances in medicine. We therefore provide an overview of curren...

OPENALEX DOI: https://doi.org/10.1097/icu.0000000000000552

Uncertainty in artificial intelligence

Simon Parsons • The Knowledge Engineering Review (1994)

The first conference on Uncertainty in Artificial Intelligence was held in 1985 by a group of people who felt that their views on the use of probability theory were not receiving a fair hearing from the rest of the Al community. At the time...

OPENALEX Open Access DOI: https://doi.org/10.1017/s0269888900006597

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

A review of optimization strategies for deep and machine learning in diabetic macular edema

A. M. Mutawa, Khalid Sabti, Bibin Shalini Sundaram Thankaleela, Seemant Raizada • Frontiers in Artificial Intelligence (2026)

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1684752

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

A satellite-derived, ground-measurement-independent monthly PM2.5 mass concentration dataset over China during 2000 - 2015

Ying Zhang, Zhengqiang Li, Yuanyuan Wei, Zongren Peng • Big Earth Data (2021)

Following the accelerated development of urbanization and industrialization, atmospheric particulate matter has become a significant threat to public health globally. Environmental health studies usually use the mass concentration of fine p...

DOAJ Open Access (DOAJ) DOI: 10.1080/20964471.2021.1918908

Artificial Intelligence and Acute Stroke Imaging

J.E. Soun, D.S. Chow, M. Nagamine, R.S. Takhtawala et al. • American Journal of Neuroradiology (2020)

Artificial intelligence technology is a rapidly expanding field with many applications in acute stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute stroke is critical for initiating prompt intervention ...

OPENALEX cc-by DOI: https://doi.org/10.3174/ajnr.a6883 PMC: 7814792

Artificial Intelligence

Christina L. McDowell Marinchak, Edward Forrest, Bogdan Hoanca • International Journal of E-Entrepreneurship and Innovation (2018)

As marketers and consumers simultaneously adopt artificial intelligence (AI) services and applications, the dynamic of the process of exchange between the buyer and seller in the marketplace is being fundamentally altered. This article revi...

OPENALEX DOI: https://doi.org/10.4018/ijeei.2018070102