AIMC Topic: Neural Networks, Computer

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Prediction of directional solidification in freeze casting of biomaterial scaffolds using physics-informed neural networks.

Biomedical physics & engineering express
Freeze casting, a manufacturing technique widely applied in biomedical fields for fabricating biomaterial scaffolds, poses challenges for predicting directional solidification due to its highly nonlinear behavior and complex interplay of process para...

Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges.

The British journal of ophthalmology
The rapid advancements in generative artificial intelligence are set to significantly influence the medical sector, particularly ophthalmology. Generative adversarial networks and diffusion models enable the creation of synthetic images, aiding the d...

Creating realistic anterior segment optical coherence tomography images using generative adversarial networks.

The British journal of ophthalmology
AIMS: To develop a generative adversarial network (GAN) capable of generating realistic high-resolution anterior segment optical coherence tomography (AS-OCT) images.

Real-Time Calibration-Free Musculotendon Kinematics for Neuromusculoskeletal Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neuromusculoskeletal (NMS) models enable non-invasive estimation of clinically important internal biomechanics. A critical part of NMS modelling is the estimation of musculotendon kinematics, which comprise musculotendon unit lengths, moment arms, an...

A Self-Supervised Equivariant Refinement Classification Network for Diabetic Retinopathy Classification.

Journal of imaging informatics in medicine
Diabetic retinopathy (DR) is a retinal disease caused by diabetes. If there is no intervention, it may even lead to blindness. Therefore, the detection of diabetic retinopathy is of great significance for preventing blindness in patients. Most of the...

Deep learning models for predicting plant uptake of emerging contaminants by including the role of plant macromolecular compositions.

Journal of hazardous materials
Deep learning models can predict uptake of emerging contaminants in plants with improved accuracy because they leverage advanced data-driven approaches to capture non-linear relationships that traditional models struggle to address. Traditional model...

Lazy Resampling: Fast and information preserving preprocessing for deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Preprocessing of data is a vital step for almost all deep learning workflows. In computer vision, manipulation of data intensity and spatial properties can improve network stability and can provide an important source of gen...

NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to ha...

Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks.

Neural networks : the official journal of the International Neural Network Society
Blood coagulation, which involves a group of complex biochemical reactions, is a crucial step in hemostasis to stop bleeding at the injury site of a blood vessel. Coagulation abnormalities, such as hypercoagulation and hypocoagulation, could either c...

Decoupling visual and identity features for adversarial palm-vein image attack.

Neural networks : the official journal of the International Neural Network Society
Palm-vein has been widely used for biometric recognition due to its resistance to theft and forgery. However, with the emergence of adversarial attacks, most existing palm-vein recognition methods are vulnerable to adversarial image attacks, and to t...