AIMC Topic: Deep Learning

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Technical Note: Quantifying music-dance synchrony during salsa dancing with a deep learning-based 2D pose estimator.

Journal of biomechanics
Dance interventions hold promise for improving gait and balance in people with neurological conditions. It is possible that synchronization of movement to the music is one of the mechanisms through which dance bestows physical benefits. This technica...

A novel deep learning model based on the ICA and Riemannian manifold for EEG-based emotion recognition.

Journal of neuroscience methods
BACKGROUND: The EEG-based emotion recognition is one of the primary research orientations in the field of emotional intelligence and human-computer interaction (HCI).

Deep learning-based transcription factor activity for stratification of breast cancer patients.

Biochimica et biophysica acta. Gene regulatory mechanisms
Transcription factors directly bind to DNA and regulate the expression of the gene, causing epigenetic modification of the DNA. They often mediate epigenetic parameters of transcriptional and posttranscriptional mechanisms, and their expression activ...

A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study.

Oral oncology
OBJECTIVE: Tissue slides from Oral cavity squamous cell carcinoma (OC-SCC), particularly the epithelial regions, hold morphologic features that are both diagnostic and prognostic. Yet, previously developed approaches for automated epithelium segmenta...

STEM Image Analysis Based on Deep Learning: Identification of Vacancy Defects and Polymorphs of MoS.

Nano letters
Scanning transmission electron microscopy (STEM) is an indispensable tool for atomic-resolution structural analysis for a wide range of materials. The conventional analysis of STEM images is an extensive hands-on process, which limits efficient handl...

Explainable Transformer-Based Deep Learning Model for the Detection of Malaria Parasites from Blood Cell Images.

Sensors (Basel, Switzerland)
Malaria is a life-threatening disease caused by female anopheles mosquito bites. Various plasmodium parasites spread in the victim's blood cells and keep their life in a critical situation. If not treated at the early stage, malaria can cause even de...

Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma.

World journal of surgical oncology
BACKGROUND: Preoperative prediction of microvascular invasion (MVI) is critical for treatment strategy making in patients with hepatocellular carcinoma (HCC). We aimed to develop a deep learning (DL) model based on preoperative dynamic contrast-enhan...

EMDLP: Ensemble multiscale deep learning model for RNA methylation site prediction.

BMC bioinformatics
BACKGROUND: Recent research recommends that epi-transcriptome regulation through post-transcriptional RNA modifications is essential for all sorts of RNA. Exact identification of RNA modification is vital for understanding their purposes and regulato...

Accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning.

Scientific reports
This study evaluates the accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning. We developed a dynamic graph convolutional neural network (DGCNN)-based algorithm for automatic tooth segmentation and clas...

Deep learning features encode interpretable morphologies within histological images.

Scientific reports
Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains...