AIMC Topic: Algorithms

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Drop edges and adapt: A fairness enforcing fine-tuning for graph neural networks.

Neural networks : the official journal of the International Neural Network Society
The rise of graph representation learning as the primary solution for many different network science tasks led to a surge of interest in the fairness of this family of methods. Link prediction, in particular, has a substantial social impact. However,...

pBRICS: A Novel Fragmentation Method for Explainable Property Prediction of Drug-Like Small Molecules.

Journal of chemical information and modeling
Generative artificial intelligence algorithms have shown to be successful in exploring large chemical spaces and designing novel and diverse molecules. There has been considerable interest in developing predictive models using artificial intelligence...

Enhanced wave overtopping simulation at vertical breakwaters using machine learning algorithms.

PloS one
Accurate prediction of wave overtopping at sea defences remains central to the protection of lives, livelihoods, and infrastructural assets in coastal zones. In addressing the increased risks of rising sea levels and more frequent storm surges, robus...

Closing the loop for AI-ready radiology.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
BACKGROUND: In recent years, AI has made significant advancements in medical diagnosis and prognosis. However, the incorporation of AI into clinical practice is still challenging and under-appreciated. We aim to demonstrate a possible vertical integr...

Value of deep learning reconstruction of chest low-dose CT for image quality improvement and lung parenchyma assessment on lung window.

European radiology
OBJECTIVES: To explore the performance of low-dose computed tomography (LDCT) with deep learning reconstruction (DLR) for the improvement of image quality and assessment of lung parenchyma.

SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for Prior-Informed Assessment of Muscle Function and Pathology.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as black boxes, exclude biomedical experts, and need extensive data. This is especially problematic for fundamental research in the laboratory, where oft...

Rapid Quantification of Microvessels of Three-Dimensional Blood-Brain Barrier Model Using Optical Coherence Tomography and Deep Learning Algorithm.

Biosensors
The blood-brain barrier (BBB) is a selective barrier that controls the transport between the blood and neural tissue features and maintains brain homeostasis to protect the central nervous system (CNS). models can be useful to understand the role of...

Artificial intelligence algorithm comparison and ranking for weight prediction in sheep.

Scientific reports
In a rapidly transforming world, farm data is growing exponentially. Realizing the importance of this data, researchers are looking for new solutions to analyse this data and make farming predictions. Artificial Intelligence, with its capacity to han...

A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results.

Journal of digital imaging
This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in improving image quality and diagnostic performance using virtual monochromatic spectral images ...

Bringing Artificial Intelligence to the operating room: edge computing for real-time surgical phase recognition.

Surgical endoscopy
BACKGROUND: Automation of surgical phase recognition is a key effort toward the development of Computer Vision (CV) algorithms, for workflow optimization and video-based assessment. CV is a form of Artificial Intelligence (AI) that allows interpretat...