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Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Heather Marriott, Renata Kabiljo, Guy P Hunt, Ahmad Al Khleifat et al. • Acta Neuropathologica Communications (2023)

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40478-023-01686-8

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

Artificial Intelligence with Uncertainty

Deyi Li, Yi Du • CRC Press eBooks (2017)

This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural la...

OPENALEX DOI: https://doi.org/10.1201/9781315366951

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

Anirban Chaudhuri, Graham Pash, David A. Hormuth, David A. Hormuth et al. • Frontiers in Artificial Intelligence (2023)

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2023.1222612

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

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

Artificial Intelligence for Efficient Thermal Comfort Systems: Requirements, Current Applications and Future Directions

Ali Ghahramani, Ali Ghahramani, Parson Galicia, David Lehrer et al. • Frontiers in Built Environment (2020)

In buildings, one or a combination of systems (e.g., central HVAC system, ceiling fan, desk fan, personal heater, and foot warmer) are often responsible for providing thermal comfort to the occupants. While thermal comfort has been shown to...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbuil.2020.00049

Optimizing Energy Consumption of Edge-Cloud Environments: A comparative Study Between PPO and PSO

Alejandro Espinosa, Xavier Samos, Daniel Ulied, Jordi Marias et al. • International Journal of Computational Intelligence Systems (2025)

Abstract As the usage of the edge-cloud continuum increases, Kubernetes presents itself as a solution that allows easy control and deployment of applications in these highly-distributed and heterogeneous environments. In this context, Artif...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-025-01073-2

Study on the impact of meteorological factors on influenza in different periods and prediction based on artificial intelligence RF-Bi-LSTM algorithm: to compare the COVID-19 period with the non-COVID-19 period

Hansong Zhu, Si Chen, Weixia Qin, Joldosh Aynur et al. • BMC Infectious Diseases (2024)

Abstract Objective At different times, public health faces various challenges and the degree of intervention measures varies. The research on the impact and prediction of meteorology factors on influenza is increasing gradually, however, th...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12879-024-09750-x

Managing Artificial Intelligence

Nicholas Berente, Bin Gu, Jan Recker, Radhika Santhanam • MIS Quarterly (2021)

Managing artificial intelligence (AI) marks the dawn of a new age of information technology management. Managing AI involves communicating, leading, coordinating, and controlling an ever-evolving frontier of computational advancements that ...

OPENALEX Open Access DOI: https://doi.org/10.25300/misq/2021/16274

Biomaterial Engineering for Spatiotemporal Regulation of Exosome Functions: From Design Principles to Key Applications in Regenerative Medicine

Shan Long, Bo Wang, Shaodong Tian, Honglan Tang et al. • Pharmaceuticals (2026)

As natural nanoscale intercellular messengers, exosomes exhibit considerable potential in modulating inflammation, angiogenesis, immunoregulation, and tissue remodeling, making them attractive candidates for regenerative medicine. However, ...

DOAJ Open Access (DOAJ) DOI: 10.3390/ph19050672

Explainable and perturbation-resilient model for cyber-threat detection in industrial control systems Networks

Urslla Uchechi Izuazu, Cosmas Ifeanyi Nwakanma, Dong-Seong Kim, Jae Min Lee • Discover Internet of Things (2025)

Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits pra...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43926-025-00100-0

The Impact of Artificial Intelligence on Innovation

Iain Cockburn, Rebecca M. Henderson, Scott Stern • National Bureau of Economic Research (2018)

Artificial intelligence may greatly increase the efficiency of the existing economy.But it may have an even larger impact by serving as a new general-purpose "method of invention" that can reshape the nature of the innovation process and th...

OPENALEX public-domain DOI: https://doi.org/10.3386/w24449