AIMC Topic: Neural Networks, Computer

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Improving Valvular Pathologies and Ventricular Dysfunction Diagnostic Efficiency Using Combined Auscultation and Electrocardiography Data: A Multimodal AI Approach.

Sensors (Basel, Switzerland)
Simple sensor-based procedures, including auscultation and electrocardiography (ECG), can facilitate early diagnosis of valvular diseases, resulting in timely treatment. This study assessed the impact of combining these sensor-based procedures with m...

DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning.

BMC bioinformatics
PURPOSE: Sequenced Protein-Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventi...

Interpretable neural architecture search and transfer learning for understanding CRISPR-Cas9 off-target enzymatic reactions.

Nature computational science
Finely tuned enzymatic pathways control cellular processes, and their dysregulation can lead to disease. Developing predictive and interpretable models for these pathways is challenging because of the complexity of the pathways and of the cellular an...

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-vel...

Phar-LSTM: a pharmacological representation-based LSTM network for drug-drug interaction extraction.

PeerJ
Pharmacological drug interactions are among the most common causes of medication errors. Many different methods have been proposed to extract drug-drug interactions from the literature to reduce medication errors over the last few years. However, the...

Deep learning-based idiomatic expression recognition for the Amharic language.

PloS one
Idiomatic expressions are built into all languages and are common in ordinary conversation. Idioms are difficult to understand because they cannot be deduced directly from the source word. Previous studies reported that idiomatic expression affects m...

A comprehensive framework for advanced protein classification and function prediction using synergistic approaches: Integrating bispectral analysis, machine learning, and deep learning.

PloS one
Proteins are fundamental components of diverse cellular systems and play crucial roles in a variety of disease processes. Consequently, it is crucial to comprehend their structure, function, and intricate interconnections. Classifying proteins into f...

Application of error level analysis in image spam classification using deep learning model.

PloS one
Image spam is a type of spam that contains text information inserted in an image file. Traditional classification systems based on feature engineering require manual extraction of certain quantitative and qualitative image features for classification...

On the compression of neural networks using ℓ-norm regularization and weight pruning.

Neural networks : the official journal of the International Neural Network Society
Despite the growing availability of high-capacity computational platforms, implementation complexity still has been a great concern for the real-world deployment of neural networks. This concern is not exclusively due to the huge costs of state-of-th...

Convolutional neural network-assisted diagnosis of midpalatal suture maturation stage in cone-beam computed tomography.

Journal of dentistry
OBJECTIVES: The selection of treatment for maxillary expansion is closely related to the calcification degree of the midpalatal suture. A classification method for individual assessment of the morphology of midpalatal suture in cone-beam computed tom...