AIMC Topic: Algorithms

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PathMLP: Smooth path towards high-order homophily.

Neural networks : the official journal of the International Neural Network Society
Real-world graphs exhibit increasing heterophily, where nodes no longer tend to be connected to nodes with the same label, challenging the homophily assumption of classical graph neural networks (GNNs) and impeding their performance. Intriguingly, fr...

The Artificial Neural Twin - Process optimization and continual learning in distributed process chains.

Neural networks : the official journal of the International Neural Network Society
Industrial process optimization and control is crucial to increase economic and ecologic efficiency. However, data sovereignty, differing goals, or the required expert knowledge for implementation impede holistic implementation. Further, the increasi...

StochCA: A novel approach for exploiting pretrained models with cross-attention.

Neural networks : the official journal of the International Neural Network Society
Utilizing large-scale pretrained models is a well-known strategy to enhance performance on various target tasks. It is typically achieved through fine-tuning pretrained models on target tasks. However, naï ve fine-tuning may not fully leverage knowle...

Metadata information and fundus image fusion neural network for hyperuricemia classification in diabetes.

Computer methods and programs in biomedicine
OBJECTIVE: In diabetes mellitus patients, hyperuricemia may lead to the development of diabetic complications, including macrovascular and microvascular dysfunction. However, the level of blood uric acid in diabetic patients is obtained by sampling p...

Zero- and few-shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials.

Research synthesis methods
Existing systems for automating the assessment of risk-of-bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of availabl...

A Deep Learning Framework for Real-Time Bird Detection and Its Implications for Reducing Bird Strike Incidents.

Sensors (Basel, Switzerland)
Bird strikes are a substantial aviation safety issue that can result in serious harm to aircraft components and even passenger deaths. In response to this increased tendency, the implementation of new and more efficient detection and prevention techn...

AI-Driven Diagnostic Assistance in Medical Inquiry: Reinforcement Learning Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: For medical diagnosis, clinicians typically begin with a patient's chief concerns, followed by questions about symptoms and medical history, physical examinations, and requests for necessary auxiliary examinations to gather comprehensive ...

RobMedNAS: searching robust neural network architectures for medical image synthesis.

Biomedical physics & engineering express
Investigating U-Net model robustness in medical image synthesis against adversarial perturbations, this study introduces RobMedNAS, a neural architecture search strategy for identifying resilient U-Net configurations. Through retrospective analysis o...

Selecting the foremost big data tool to optimize YouTube data in dynamic Fermatean fuzzy knowledge.

PloS one
Big data pertains to extensive and intricate compilations of information that necessitate the implementation of proficient and cost-effective evaluation and analysis tools to derive insights and support decision making. The Fermatean fuzzy set theory...

Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.

PloS one
AIM: In this review, we investigated how Machine Learning (ML) was utilized to predict all-cause somatic hospital admissions and readmissions in adults.