AIMC Topic: Deep Learning

Clear Filters Showing 6351 to 6360 of 28423 articles

A Fully Automated Pipeline Using Swin Transformers for Deep Learning-Based Blood Segmentation on Head Computed Tomography Scans After Aneurysmal Subarachnoid Hemorrhage.

World neurosurgery
BACKGROUND: Accurate volumetric assessment of spontaneous aneurysmal subarachnoid hemorrhage (aSAH) is a labor-intensive task performed with current manual and semiautomatic methods that might be relevant for its clinical and prognostic implications....

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

Genomics
This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neu...

Brain-GCN-Net: Graph-Convolutional Neural Network for brain tumor identification.

Computers in biology and medicine
BACKGROUND: The intersection of artificial intelligence and medical image analysis has ushered in a new era of innovation and changed the landscape of brain tumor detection and diagnosis. Correct detection and classification of brain tumors based on ...

Geometric deep learning of protein-DNA binding specificity.

Nature methods
Predicting protein-DNA binding specificity is a challenging yet essential task for understanding gene regulation. Protein-DNA complexes usually exhibit binding to a selected DNA target site, whereas a protein binds, with varying degrees of binding sp...

Single-detector multiplex imaging flow cytometry for cancer cell classification with deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Imaging flow cytometry, which combines the advantages of flow cytometry and microscopy, has emerged as a powerful tool for cell analysis in various biomedical fields such as cancer detection. In this study, we develop multiplex imaging flow cytometry...

Deep-learning-based design of synthetic orthologs of SH3 signaling domains.

Cell systems
Evolution-based deep generative models represent an exciting direction in understanding and designing proteins. An open question is whether such models can learn specialized functional constraints that control fitness in specific biological contexts....

Deep Learning System for User Identification Using Sensors on Doorknobs.

Sensors (Basel, Switzerland)
Door access control systems are important to protect the security and integrity of physical spaces. Accuracy and speed are important factors that govern their performance. In this paper, we investigate a novel approach to identify users by measuring ...

An improved data augmentation approach and its application in medical named entity recognition.

BMC medical informatics and decision making
Performing data augmentation in medical named entity recognition (NER) is crucial due to the unique challenges posed by this field. Medical data is characterized by high acquisition costs, specialized terminology, imbalanced distributions, and limite...

The impact of deep learning based- psychological capital with ideological and political education on entrepreneurial intentions.

Scientific reports
The aim of this study is to investigate the influence of psychological capital on college students' entrepreneurial intentions. Through a combination of relevant analysis and linear regression, the primary focus is on exploring the relationship betwe...