Computed tomography (CT) is a major medical imaging modality. Clinical CT scenarios, such as low-dose screening, sparse-view scanning, and metal implants, often lead to severe noise and artifacts in reconstructed images, requiring improved reconstruc... read more
BACKGROUND: Artificial neural networks (ANNs) are increasingly applied in health care outcome prediction, yet their relative benefits compared with traditional methods in health services research remain unclear. OBJECTIVE: To examine health care util... read more
PURPOSE: Early-stage lung adenocarcinoma (LUAD) exhibits substantial clinical heterogeneity that is not fully explained by TNM staging, highlighting the need for biology-driven prognostic tools. Although metabolic reprogramming is an established canc... read more
PURPOSE: To develop and validate machine learning (ML) models for postoperative risk stratification in oral cavity squamous cell carcinoma (OCSCC) and to examine whether ML-derived risk groups modify the association between adjuvant therapy and overa... read more
The rapid growth of artificial intelligence (AI) is increasingly constrained by fundamental hardware bottlenecks in computation throughput and energy efficiency. Bioinspired computing (BIC) offers a promising alternative by emulating the intrinsic ad... read more
Collective behavior, emerging from interactions among individuals, is a ubiquitous phenomenon observed across a wide range of biological systems-from cellular dynamics to animal ecology. Network science offers powerful tools for understanding the str... read more
European heart journal. Digital health
Mar 2, 2026
AIMS: All-cause mortality ranges between 33% and 42% for individuals with untreated moderate to severe aortic stenosis (AS). Transcatheter aortic valve replacement makes this a treatable condition, if identified early. Machine learning-based tools sh... read more
Neural networks : the official journal of the International Neural Network Society
Mar 2, 2026
Multi-view clustering has become an effective tool for integrating complementary information from multiple data sources. However, traditional clustering methods often struggle with computational efficiency, as well as capturing high-order correlation... read more
Neural networks : the official journal of the International Neural Network Society
Mar 2, 2026
Graph-structured data has emerged as a crucial tool for representing complex systems in various domains. The analysis of such data entails addressing two fundamental problems: attributed graph clustering and semi-supervised node classification. This ... read more
The lethal concentration (LC50) of Daphnia is a significant toxicity index for water quality assessment and chemical management; however, obtaining LC50 values for all substances poses difficulties in terms of cost and time. This study developed a de... read more
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