AIMC Topic: Deep Learning

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Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients.

Cancer medicine
BACKGROUND: Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistoc...

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening.

Respiratory research
OBJECTIVES: Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT scans. We hypothesize that deep learning PRM from inspiratory chest CT scans ...

Comparison of deep learning-based image segmentation methods for intravascular ultrasound on retrospective and large image cohort study.

Biomedical engineering online
OBJECTIVES: The aim of this study was to investigate the generalization performance of deep learning segmentation models on a large cohort intravascular ultrasound (IVUS) image dataset over the lumen and external elastic membrane (EEM), and to assess...

Deep learning model for measuring the sagittal Cobb angle on cervical spine computed tomography.

BMC medical imaging
PURPOSES: To develop a deep learning (DL) model to measure the sagittal Cobb angle of the cervical spine on computed tomography (CT).

PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features.

Scientific reports
Protein-peptide interactions play a crucial role in various cellular processes and are implicated in abnormal cellular behaviors leading to diseases such as cancer. Therefore, understanding these interactions is vital for both functional genomics and...

Label-free identification of protein aggregates using deep learning.

Nature communications
Protein misfolding and aggregation play central roles in the pathogenesis of various neurodegenerative diseases (NDDs), including Huntington's disease, which is caused by a genetic mutation in exon 1 of the Huntingtin protein (Httex1). The fluorescen...

verified anatomically aware deep learning for real-time electric field simulation.

Journal of neural engineering
Transcranial magnetic stimulation (TMS) has emerged as a prominent non-invasive technique for modulating brain function and treating mental disorders. By generating a high-precision magnetically evoked electric field (E-field) using a TMS coil, it en...

MAG-Res2Net: a novel deep learning network for human activity recognition.

Physiological measurement
Human activity recognition (HAR) has become increasingly important in healthcare, sports, and fitness domains due to its wide range of applications. However, existing deep learning based HAR methods often overlook the challenges posed by the diversit...

Multicenter Study of the Utility of Convolutional Neural Network and Transformer Models for the Detection and Segmentation of Meningiomas.

Journal of computer assisted tomography
PURPOSE: This study aimed to investigate the effectiveness and practicality of using models like convolutional neural network and transformer in detecting and precise segmenting meningioma from magnetic resonance images.