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ABSTRACT Background and Aim As dental anomalies can significantly affect esthetic and function, early detection and diagnosis are crucial for treatment and minimizing potential negative effects. Artificial intelligence (...

With the great developments in optical communication technology and large-scale optical integration technology, it is imperative to realize the traditional functions of polarization processing on an integration platform....

ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective s...

ABSTRACT Analysing learners' facial expressions during learning and exploring their learning processes and emotional changes are of great significance for assisting teachers' teaching and promoting smart education. In co...

ABSTRACT Graph contrastive learning (GCL) has emerged as a dominant paradigm for self‐supervised representation learning for attributed graph data. However, existing GCL methods heavily rely on empirical graph data aug...

ABSTRACT This paper presents HealthNet, a novel framework for the dynamic optimisation of healthcare transportation networks using multi‐agent reinforcement learning. HealthNet leverages a spatiotemporal dependency mod...

ABSTRACT Integrating healthcare systems with intelligent transportation networks represents a critical frontier in modern urban infrastructure, where efficient resource allocation and timely service delivery can signific...

Abstract Rapid identification of bacterial species from patient samples is crucial for clinical decision‐making. In severe infections, such as bloodstream infections, the early start of an effective treatment is direct...

ABSTRACT Plant diseases are the cause of heavy losses of crop production and, therefore, a big contributor to food shortages. Identifying these diseases as early as possible is important to limit the negative effects tha...