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Assessing carbon and economic loss from oak decline in Iran’s Zagros forests using Sentinel-2 and machine learning

Saied Pirasteh, Zohreh Bazvand, Naseh Miri, Zhaoxi Fang et al. • Geo-spatial Information Science (2026)

Over recent decades, the decline of oak trees, which has emerged as the most significant challenge to the Zagros forests (ZFs), poses serious threats to carbon storage (CS) and economic valuation, jeopardizing the ecological and economic su...

DOAJ Open Access (DOAJ) DOI: 10.1080/10095020.2026.2682739

Mapping artificial intelligence research in higher education toward sustainable development

Tieu Thi My Hong, Nguyen Thi Thanh Tung, Nguyen Thi Phuong Thanh • Discover Sustainability (2025)

Abstract The rapid development of Artificial Intelligence (AI) has had a profound impact on higher education (HE), fundamentally changing teaching, learning, research and academic management. Although there have been many studies on the app...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-025-02162-0

Artificial intelligence tools in dermatology education: A scoping review on their application, efficacy, and limitations

Chun Hian John Yap, Ziying Vanessa Lim • Annals, Academy of Medicine, Singapore (2026)

Introduction: Artificial Intelligence (AI) is increasingly explored for medical education, and dermatology, with its visual diagnostic focus, holds promise for AI-enhanced learning. However, evidence on its educational effectiveness remains...

DOAJ Open Access (DOAJ) DOI: 10.47102/annals-acadmedsg.2026346

Authentic content as an effective mechanism for embedding patient voices in health innovation: a hypothesis and conceptual framework

Rohin Malhotra • Frontiers in Health Services (2026)

Health innovation systems continue to face persistent inefficiencies, mistrust, and escalating development costs despite rapid scientific progress. Although patient-engagement is increasingly recognised as essential for patient-centred heal...

DOAJ Open Access (DOAJ) DOI: 10.3389/frhs.2026.1833920

AI Review Bots vs. Humans in Handling Negative Reviews: Who Builds More Trust?

Yizhen Wei, David (Jingjun) Xu, Kai Li • Journal of Theoretical and Applied Electronic Commerce Research (2026)

As artificial intelligence (AI) increasingly engages in managing consumer interactions on e-commerce platforms, an important question arises: how do public AI-generated replies to negative reviews compare with human replies in fostering con...

DOAJ Open Access (DOAJ) DOI: 10.3390/jtaer21030094

Governance of artificial intelligence

Araz Taeihagh • Policy and Society (2021)

ABSTRACT The rapid developments in Artificial Intelligence (AI) and the intensification in the adoption of AI in domains such as autonomous vehicles, lethal weapon systems, robotics and alike pose serious challenges to governments as they m...

OPENALEX cc-by-nc DOI: https://doi.org/10.1080/14494035.2021.1928377

Innovation and Design in the Age of Artificial Intelligence

Roberto Verganti, Luca Vendraminelli, Marco Iansiti • Journal of Product Innovation Management (2020)

At the heart of any innovation process lies a fundamental practice: the way people create ideas and solve problems. This “decision making” side of innovation is what scholars and practitioners refer to as “design.” Decisions in innovation p...

OPENALEX cc-by DOI: https://doi.org/10.1111/jpim.12523

Artificial intelligence and machine learning

Niklas Kühl, Max Schemmer, Marc Goutier, Gerhard Satzger • Electronic Markets (2022)

Abstract Within the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s12525-022-00598-0

Artificial Intelligence and Systemic Risk

Jón Danı́elsson, Robert Macrae, Andreas Uthemann • Journal of Banking & Finance (2019)

Artificial intelligence (AI) is rapidly changing how the financial system is operated, taking over core functions for both cost savings and operational efficiency reasons. AI will assist both risk managers and the financial authorities. How...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.jbankfin.2021.106290

The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

Yuri Yin‐Moe Aung, David Wong, Daniel Shu Wei Ting • British Medical Bulletin (2021)

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and...

OPENALEX DOI: https://doi.org/10.1093/bmb/ldab016

Artificial Intelligence, Simulation, and Modeling

Lawrence E. Widman, Kenneth A. Loparo • INFORMS Journal on Applied Analytics (1990)

Artificial intelligence and simulation overlap increasingly as computer hardware prices fall and software sophistication increases. Artificial intelligence programming methods permit more realistic and robust simulation models and help the ...

OPENALEX DOI: https://doi.org/10.1287/inte.20.2.48

What radiologists need to know about patients’ expectations: P.A.T.I.E.N.T.S C.A.R.E.R.S A.I.M.S

European Society of Radiology (ESR) • Insights into Imaging (2022)

Abstract The Patient Advisory Group (PAG) of the European Society of Radiology aims to highlight, in this short paper, patients’ expectations from the radiological community and support workers, throughout the patient’s medical imaging jour...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13244-022-01184-w

APRICOIN: An Adaptive Approach for Prioritizing High-Risk Containers Inspections

Mohamed Yassine Samiri, Mehdi Najib, Abdelaziz Elfazziki, Mohamed Nezar Abourraja et al. • IEEE Access (2017)

Risk evaluation of the containers remains a difficult task, often due to incomplete or ambiguous information on containers. In addition, the evaluation process needs to be adapted on an ongoing basis to cope with emerging risk factors. Furt...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2017.2746838

Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

Ebtisam AlJalaud, Manar Hosny • Mathematics (2024)

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior...

DOAJ Open Access (DOAJ) DOI: 10.3390/math12233727