AIMC Topic: Neural Networks, Computer

Clear Filters Showing 28131 to 28140 of 31376 articles

Quantitative level determination of fixed restorations on panoramic radiographs using deep learning.

International journal of computerized dentistry
AIM: Although many studies in various fields employ deep learning models, only a few such studies exist in dental imaging. The present article aims to evaluate the effectiveness of convolutional neural network (CNN) algorithms for the detection and d...

An artificial intelligence model for instance segmentation and tooth numbering on orthopantomograms.

International journal of computerized dentistry
AIM: To develop a deep learning (DL) artificial intelligence (AI) model for instance segmentation and tooth numbering on orthopantomograms (OPGs).

Research on Brain Signals Classification Based on Deep Learning.

Studies in health technology and informatics
With the continuous expansion of brain-computer communication, the precise identification of brain signals has become an essential task for brain-computer equipment. However, existing classification methods are primarily concentrated on the extractio...

Using SimAM and SSD to Detect Prostate Capsule.

Studies in health technology and informatics
Aiming at the problem of accurate detection of the prostate capsule, this paper designed an accurate detection network of the prostate capsule by integrating 3d non-parametric residual attention mechanism SimAM and SSD, whcih called Attention based o...

Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs.

Briefings in bioinformatics
Exploring microbial stress responses to drugs is crucial for the advancement of new therapeutic methods. While current artificial intelligence methodologies have expedited our understanding of potential microbial responses to drugs, the models are co...

Explainable artificial intelligence for omics data: a systematic mapping study.

Briefings in bioinformatics
Researchers increasingly turn to explainable artificial intelligence (XAI) to analyze omics data and gain insights into the underlying biological processes. Yet, given the interdisciplinary nature of the field, many findings have only been shared in ...

MESPool: Molecular Edge Shrinkage Pooling for hierarchical molecular representation learning and property prediction.

Briefings in bioinformatics
Identifying task-relevant structures is important for molecular property prediction. In a graph neural network (GNN), graph pooling can group nodes and hierarchically represent the molecular graph. However, previous pooling methods either drop out no...

BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation.

Briefings in bioinformatics
Although substantial efforts have been made using graph neural networks (GNNs) for artificial intelligence (AI)-driven drug discovery, effective molecular representation learning remains an open challenge, especially in the case of insufficient label...

Assessing protein model quality based on deep graph coupled networks using protein language model.

Briefings in bioinformatics
Model quality evaluation is a crucial part of protein structural biology. How to distinguish high-quality models from low-quality models, and to assess which high-quality models have relatively incorrect regions for improvement, are remain a challeng...

Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Use heuristic, deep learning (DL), and hybrid AI methods to predict semantic group (SG) assignments for new UMLS Metathesaurus atoms, with target accuracy ≥95%.