AIMC Topic: Algorithms

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Data reduction for SVM training using density-based border identification.

PloS one
Numerous classification and regression problems have extensively used Support Vector Machines (SVMs). However, the SVM approach is less practical for large datasets because of its processing cost. This is primarily due to the requirement of optimizin...

LMGATCDA: Graph Neural Network With Labeling Trick for Predicting circRNA-Disease Associations.

IEEE/ACM transactions on computational biology and bioinformatics
Previous studies have proven that circular RNAs (circRNAs) are inextricably connected to the etiology and pathophysiology of complicated diseases. Since conventional biological research are frequently small-scale, expensive, and time-consuming, it is...

The new era of artificial intelligence in neuroradiology: current research and promising tools.

Arquivos de neuro-psiquiatria
Radiology has a number of characteristics that make it an especially suitable medical discipline for early artificial intelligence (AI) adoption. These include having a well-established digital workflow, standardized protocols for image storage, and ...

H2MaT-Unet:Hierarchical hybrid multi-axis transformer based Unet for medical image segmentation.

Computers in biology and medicine
Accurate segmentation and lesion localization are essential for treating diseases in medical images. Despite deep learning methods enhancing segmentation, they still have limitations due to convolutional neural networks' inability to capture long-ran...

Comparative analysis of the spatial distribution of brain metastases across several primary cancers using machine learning and deep learning models.

Journal of neuro-oncology
OBJECTIVE: Brain metastases (BM) are associated with poor prognosis and increased mortality rates, making them a significant clinical challenge. Studying BMs can aid in improving early detection and monitoring. Systematic comparisons of anatomical di...

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions.

Tomography (Ann Arbor, Mich.)
To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conduc...

Electrocardiography-based Artificial Intelligence Algorithms Aid in Prediction of Long-term Mortality After Kidney Transplantation.

Transplantation
BACKGROUND: Predicting long-term mortality postkidney transplantation (KT) using baseline clinical data presents significant challenges. This study aims to evaluate the predictive power of artificial intelligence (AI)-enabled analysis of preoperative...

Structural deep multi-view clustering with integrated abstraction and detail.

Neural networks : the official journal of the International Neural Network Society
Deep multi-view clustering, which can obtain complementary information from different views, has received considerable attention in recent years. Although some efforts have been made and achieve decent performances, most of them overlook the structur...

A novel interactive deep cascade spectral graph convolutional network with multi-relational graphs for disease prediction.

Neural networks : the official journal of the International Neural Network Society
Graph neural networks (GNNs) have recently grown in popularity for disease prediction. Existing GNN-based methods primarily build the graph topological structure around a single modality and combine it with other modalities to acquire feature represe...

Using neural networks to autonomously assess adequacy in intraoperative cholangiograms.

Surgical endoscopy
BACKGROUND: Intraoperative cholangiography (IOC) is a contrast-enhanced X-ray acquired during laparoscopic cholecystectomy. IOC images the biliary tree whereby filling defects, anatomical anomalies and duct injuries can be identified. In Australia, I...