Results 121 to 130 of about 55,142 (282)
Artificial intelligence (AI) offers transformative potential for paediatric diagnosis and treatment, yet implementation faces unique challenges, including data scarcity, algorithmic bias, and children's developmental physiology. This review examines current applications and charts a path toward transparent, equitable, and trustworthy AI in child health.
Ruisong Wang +3 more
wiley +1 more source
ABSTRACT High‐resolution mapping of permafrost in ecologically and topographically complex landscapes remains a major challenge. Existing models of permafrost extent often rely on equilibrium assumptions, which can misrepresent conditions in regions where permafrost persists largely due to ecosystem structure.
Philip P. Bonnaventure +3 more
wiley +1 more source
Machine learning‐based predictive models outperform traditional risk scores in hemodialysis patients with comorbid urolithiasis by capturing nonlinear, dialysis‐specific interactions. These approaches enable more accurate prediction of stone recurrence, sepsis, hospitalization, and mortality, supporting personalized risk stratification and precision ...
Dipal Chaulagain +4 more
wiley +1 more source
In this research, we hypothesize that attitudes toward artificial intelligence (AI) are shaped by individuals’ perceived competence in using and managing it, as well as their assessment of the importance of AI’s understandability and transparency, often ...
M. Liebherr +5 more
doaj +1 more source
The recent advancements in autonomous driving come with the associated cybersecurity issue of compromising networks of autonomous vehicles (AVs), motivating the use of AI models for detecting anomalies on these networks.
Sazid Nazat +2 more
doaj +1 more source
ABSTRACT Sustainable livestock manure management sits at the nexus of climate, nutrient circularity and water quality. This review explores how artificial intelligence (AI) and digital platforms are used across four management stages, that is, treatment, storage, valorisation and distribution, and figures out where integration fails to deliver ...
Zhan Shi +3 more
wiley +1 more source
Explainable Artificial Intelligence for Drug Discovery and Development: A Comprehensive Survey
The field of drug discovery has experienced a remarkable transformation with the advent of artificial intelligence (AI) and machine learning (ML) technologies.
Roohallah Alizadehsani +7 more
doaj +1 more source
XAI and Android Malware Models
Android malware detection based on machine learning (ML) and deep learning (DL) models is widely used for mobile device security. Such models offer benefits in terms of detection accuracy and efficiency, but it is often difficult to understand how such learning models make decisions. As a result, these popular malware detection strategies are generally
Maithili Kulkarni, Mark Stamp
openaire +2 more sources
ABSTRACT Rapid urbanisation and intensifying rainfall have increased cities' vulnerability to flooding, posing major challenges to sustainable development. Although machine learning models have improved flood prediction accuracy, most remain limited by their black‐box nature and lack of actionable insights.
Abdulwaheed Tella +4 more
wiley +1 more source
AI‐Driven Circular Construction Waste Management for Advancing Sustainable Development
ABSTRACT Construction and demolition waste (C&DW) represents up to 40% of global solid waste, posing a significant barrier to achieving circular economy (CE) objectives and the Sustainable Development Goals (SDGs), particularly SDG 11 and SDG 12. However, construction waste management (CWM) systems remain constrained by fragmented data environments ...
Mohamed T. Elnabwy, Pablo Martinez
wiley +1 more source

