Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4319395 | PMC |
| http://dx.doi.org/10.3389/fnhum.2015.00054 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Directional Spatial and Spectral Attention Network (DSSA Net) for EEG-based emotion recognition.
Front Neurorobot
January 2025
School of Computer Science, Northwestern Polytechnical University, Xi'an, China.
Significant strides have been made in emotion recognition from Electroencephalography (EEG) signals. However, effectively modeling the diverse spatial, spectral, and temporal features of multi-channel brain signals remains a challenge. This paper proposes a novel framework, the Directional Spatial and Spectral Attention Network (DSSA Net), which enhances emotion recognition accuracy by capturing critical spatial-spectral-temporal features from EEG signals.
View Article and Find Full Text PDFMid-infrared spectra of dried and roasted cocoa ( L.): A dataset for machine learning-based classification of cocoa varieties and prediction of theobromine and caffeine content.
Data Brief
February 2025
Centro Surcolombiano de Investigación en Café (CESURCAFÉ), Departamento de Ingeniería Agrícola, Universidad Surcolombiana, Neiva-Huila 410001, Colombia.
This paper presents a comprehensive dataset of mid-infrared spectra for dried and roasted cocoa beans ( L.), along with their corresponding theobromine and caffeine content. Infrared data were acquired using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy, while High-Performance Liquid Chromatography (HPLC) was employed to accurately quantify theobromine and caffeine in the dried cocoa beans.
View Article and Find Full Text PDFEthics of Procuring and Using Organs or Tissue from Infants and Newborns for Transplantation, Research, or Commercial Purposes: Protocol for a Bioethics Scoping Review.
Wellcome Open Res
December 2024
National University of Singapore, Singapore, Singapore.
Unlabelled: Since the inception of transplantation, it has been crucial to ensure that organ or tissue donations are made with valid informed consent to avoid concerns about coercion or exploitation. This issue is particularly challenging when it comes to infants and younger children, insofar as they are unable to provide consent. Despite their vulnerability, infants' organs and tissues are considered valuable for biomedical purposes due to their size and unique properties.
View Article and Find Full Text PDFRobust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets.
Front Artif Intell
January 2025
Department of Computer and Automatic Control, Faculty of Engineering, Tanta University, Tanta, Egypt.
Introduction: Diabetes prediction using clinical datasets is crucial for medical data analysis. However, class imbalances, where non-diabetic cases dominate, can significantly affect machine learning model performance, leading to biased predictions and reduced generalization.
Methods: A novel predictive framework employing cutting-edge machine learning algorithms and advanced imbalance handling techniques was developed.
A multi-patch-based deep learning model with VGG19 for breast cancer classifications in the pathology images.
Digit Health
January 2025
School of IT and Engineering, Melbourne Institute of Technology, Melbourne, Australia.
Purpose: Breast cancer encompasses various subtypes with distinct prognoses, necessitating accurate stratification methods. Current techniques rely on quantifying gene expression in limited subsets. Given the complexity of breast tissues, effective detection and classification of breast cancer is crucial in medical imaging.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!