AIMC Topic: Convolutional Neural Networks

Clear Filters Showing 1 to 10 of 402 articles

Flemboda artificial intelligence: hybrid fuzzy-convolutional neural network for efficient chromosome abnormality classification.

Molecular genetics and genomics : MGG
Chromosomal abnormality detection is a fundamental task in clinical genetics, as accurate identification of structural and numerical defects is essential for reliable diagnosis and treatment planning. However, many existing learning-based approaches ...

Automated retinal disease classification using deep learning and AlexNet with statistical models analysis.

PloS one
Diabetic Retinopathy, Cataract, and Glaucoma are major retinal diseases that require early detection to prevent irreversible vision loss. This study proposes a deep learning-based framework for the automated classification of retinal images into four...

Boosting living spore identification: Kolmogorov-Arnold network-guided convolutional neural network combined with laser tweezers Raman spectroscopy.

The Analyst
As primary carriers of foodborne and zoonotic diseases, spores can pose a serious threat to food microbiology and human disease. Thus, the precise identification of spores is of great significance for ensuring food safety and human health. Herein, ...

Automatic classification of uveal melanoma response patterns following ruthenium-106 plaque brachytherapy using ultrasound images and deep convolutional neural network.

Scientific reports
Following uveal melanoma (UM) affected treatment using ruthenium-106 brachytherapy, tumor thickness patterns fall into one of four categories: decrease (regression), increase (recurrence), stop (stable), or other, which are assessed in follow-up A-mo...

Application of Fully Convolutional Neural Networks in the Assessment of Cerebral White Matter Involvement in Primary Sjögren's Syndrome.

Neuroinformatics
Central nervous system (CNS) involvement in primary Sjögren's syndrome (pSS), although less frequent, can lead to serious complications. Our study aimed to assess white matter (WM) tract integrity, identify specific regions of disruption, quantify di...

Subtype classification of gastric spindle cell tumors in whole slide images.

Computers in biology and medicine
AIMS: Accurate cancer subtype classification is critical due to variations in tumor progression and prognosis. Traditionally, pathologists classified subtypes manually by examining pathological slides under the microscope. To address increasing workl...

Automated cementing quality detection using a domain-specific, multi-scale convolutional neural network.

PloS one
Cementing quality is a key factor in ensuring the long-term safe production of oil and gas wells and preventing defects. Traditional cementing quality evaluation mainly relies on logging interpreters manually analyzing acoustic logging data, such as ...

Mobile phone-based plasmodium parasites stage detection from Giemsa stained blood smear by convolutional neural networks.

Parasitology research
Plasmodium vivax is a malaria parasite with a broad geographic distribution worldwide. The unique biological characteristics of P. vivax, such as early gametocytogenesis and its latent hypnozoite stage, make it more difficult to control compared to P...

Accurate prediction of protein-ATP binding sites based on a protein pretrained large language model and a fractional-order convolutional neural network.

Scientific reports
ATP, a high-energy phosphate compound also known as adenosine triphosphate, serves as a direct energy source for living organisms. Proteins, composed of amino acids, are fundamental macromolecules and essential building blocks of life. The interactio...