AIMC Topic: Neural Networks, Computer

Clear Filters Showing 1031 to 1040 of 31376 articles

Automated identification of sedimentary structures in core images using object detection algorithms.

PloS one
Manual interpretation of sedimentary structures in core-based analyses is critical for understanding subsurface geology but remains time-intensive, expert-dependent, and susceptible to bias. This study investigates the use of convolutional neural net...

Explainable Graph Neural Networks in Chemistry: Combining Attribution and Uncertainty Quantification.

Journal of chemical information and modeling
Graph Neural Networks (GNNs) are powerful tools for predicting chemical properties, but their black-box nature can limit trust and utility. Explainability through feature attribution and awareness of prediction uncertainty are critical for practical ...

Graph Convolutional Neural Network-Enabled Frontier Molecular Orbital Prediction: A Case Study with Neurotransmitters and Antidepressants.

Journal of chemical information and modeling
With the advancement of artificial intelligence-embedded methodologies, their application to predict fundamental molecular properties has become increasingly prevalent. In this study, a graph convolutional neural network fingerprint-enabled artificia...

Electrocardiographic sex index: a continuous representation of sex.

Biology of sex differences
Clinical risk calculators consider sex as a binary variable. However, sex is a complex trait with anatomic, physiologic, and metabolic attributes that are not easily summarized in this manner [1]. We propose a continuous representation of sex, the EC...

Ensemble learning for microbiome-based caries diagnosis: multi-group modeling and biological interpretation from salivary and plaque metagenomic data.

BMC oral health
BACKGROUND: Oral microbiota is a major etiological factor in the development of dental caries. Next-generation sequencing techniques have been widely used, generating vast amounts of data which is underexplored. The advancement of artificial intellig...

Machine learning analysis of drug solubility via green approach to enhance drug solubility for poor soluble medications in continuous manufacturing.

Scientific reports
The development of continuous pharmaceutical manufacturing is crucial and can be analyzed via advanced computational models. Machine learning is a strong computational paradigm that can be integrated into a continuous process to enhance the drugs' so...

An AI method to predict pregnancy loss by extracting biological indicators from embryo ultrasound recordings in early pregnancy.

Scientific reports
B-ultrasound results are widely used in early pregnancy loss (EPL) prediction, but there are inevitable intra-observer and inter-observer errors in B-ultrasound results especially in early pregnancy, which lead to inconsistent assessment of embryonic...

Deep learning models for deriving optimised measures of fat and muscle mass from MRI.

Scientific reports
Fat and muscle mass are potential biomarkers of wellbeing and disease in oncology, but clinical measurement methods vary considerably. Here we evaluate the accuracy, precision and ability to track change for multiple deep learning (DL) models that qu...

FLPneXAINet: Federated deep learning and explainable AI for improved pneumonia prediction utilizing GAN-augmented chest X-ray data.

PloS one
Pneumonia, a severe lung infection caused by various viruses, presents significant challenges in diagnosis and treatment due to its similarities with other respiratory conditions. Additionally, the need to protect patient privacy complicates the shar...

SML-Net: Semi-supervised multi-task learning network for carotid plaque segmentation and classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Carotid ultrasound image segmentation and classification are crucial in assessing the severity of carotid plaques which serve as a major cause of ischemic stroke. Although many methods are employed for carotid plaque segmentation and classification, ...