AIMC Topic: Databases, Factual

Clear Filters Showing 1981 to 1990 of 3080 articles

ECG authentication system design incorporating a convolutional neural network and generalized S-Transformation.

Computers in biology and medicine
Electrocardiogram (ECG) is gaining increased attention as a biometric method in a wide range of applications, such as access control and security/privacy requirements. The majority of reported investigations using the ECG biometric method are usually...

A Hybrid Feature Selection Method Based on Binary State Transition Algorithm and ReliefF.

IEEE journal of biomedical and health informatics
Feature selection problems often appear in the application of data mining, which have been difficult to handle due to the NP-hard property of these problems. In this study, a simple but efficient hybrid feature selection method is proposed based on b...

A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation.

IEEE journal of biomedical and health informatics
Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye-related diseases, in which both thick vessels and thin vessels are important features for symptom detection. All existing deep learning models attempt to segment both...

Aiding the Digital Mammogram for Detecting the Breast Cancer Using Shearlet Transform and Neural Network.

Asian Pacific journal of cancer prevention : APJCP
Objective: Breast Cancer is the most invasive disease and fatal disease next to lung cancer in human. Early detection of breast cancer is accomplished by X-ray mammography. Mammography is the most effective and efficient technique used for detection ...

Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Effective utilization of multi-center data for autism spectrum disorder (ASD) diagnosis recently has attracted increasing attention, since a large number of subjects from multiple centers are beneficial for investigating the pathological changes of A...

Deep learning-based transcriptome data classification for drug-target interaction prediction.

BMC genomics
BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded...

Registration-Based Organ Positioning and Joint Segmentation Method for Liver and Tumor Segmentation.

BioMed research international
The automated segmentation of liver and tumor from CT images is of great importance in medical diagnoses and clinical treatment. However, accurate and automatic segmentation of liver and tumor is generally complicated due to the complex anatomical st...

Machine learning ensemble models predict total charges and drivers of cost for transsphenoidal surgery for pituitary tumor.

Journal of neurosurgery
OBJECTIVE: Efficient allocation of resources in the healthcare system enables providers to care for more and needier patients. Identifying drivers of total charges for transsphenoidal surgery (TSS) for pituitary tumors, which are poorly understood, r...

Emergence of Binocular Disparity Selectivity through Hebbian Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Földiák, 1989;...

Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection.

Neural networks : the official journal of the International Neural Network Society
As humans we possess an intuitive ability for navigation which we master through years of practice; however existing approaches to model this trait for diverse tasks including monitoring pedestrian flow and detecting abnormal events have been limited...