AIMC Topic: Neural Networks, Computer

Clear Filters Showing 6791 to 6800 of 31376 articles

BACK-to-MOVE: Machine learning and computer vision model automating clinical classification of non-specific low back pain for personalised management.

PloS one
BACKGROUND: Low back pain (LBP) is a major global disability contributor with profound health and socio-economic implications. The predominant form is non-specific LBP (NSLBP), lacking treatable pathology. Active physical interventions tailored to in...

Engineering mannose-functionalized nanostructured lipid carriers by sequential design using hybrid artificial intelligence tools.

Drug delivery and translational research
Nanostructured lipid carriers (NLCs) hold significant promise as drug delivery systems (DDS) owing to their small size and efficient drug-loading capabilities. Surface functionalization of NLCs can facilitate interaction with specific cell receptors,...

Robust Automated Tumour Segmentation Network Using 3D Direction-Wise Convolution and Transformer.

Journal of imaging informatics in medicine
Semantic segmentation of tumours plays a crucial role in fundamental medical image analysis and has a significant impact on cancer diagnosis and treatment planning. UNet and its variants have achieved state-of-the-art results on various 2D and 3D med...

PSFHSP-Net: an efficient lightweight network for identifying pubic symphysis-fetal head standard plane from intrapartum ultrasound images.

Medical & biological engineering & computing
The accurate selection of the ultrasound plane for the fetal head and pubic symphysis is critical for precisely measuring the angle of progression. The traditional method depends heavily on sonographers manually selecting the imaging plane. This proc...

A Multi-Level Relation-Aware Transformer model for occluded person re-identification.

Neural networks : the official journal of the International Neural Network Society
Occluded person re-identification (Re-ID) is a challenging task, as pedestrians are often obstructed by various occlusions, such as non-pedestrian objects or non-target pedestrians. Previous methods have heavily relied on auxiliary models to obtain i...

Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its performance with traditional Cox regression.

ProBAN: Neural network algorithm for predicting binding affinity in protein-protein complexes.

Proteins
Determining binding affinities in protein-protein and protein-peptide complexes is a challenging task that directly impacts the development of peptide and protein pharmaceuticals. Although several models have been proposed to predict the value of the...

A nursing note-aware deep neural network for predicting mortality risk after hospital discharge.

International journal of nursing studies
BACKGROUND: ICU readmissions and post-discharge mortality pose significant challenges. Previous studies used EHRs and machine learning models, but mostly focused on structured data. Nursing records contain crucial unstructured information, but their ...

Learning dynamic graph representations through timespan view contrasts.

Neural networks : the official journal of the International Neural Network Society
The rich information underlying graphs has inspired further investigation of unsupervised graph representation. Existing studies mainly depend on node features and topological properties within static graphs to create self-supervised signals, neglect...

An efficient deep neural network for automatic classification of acute intracranial hemorrhages in brain CT scans.

Computers in biology and medicine
BACKGROUND: Recent advancements in deep learning models have demonstrated their potential in the field of medical imaging, achieving remarkable performance surpassing human capabilities in tasks such as classification and segmentation. However, these...