AIMC Topic: Algorithms

Clear Filters Showing 14611 to 14620 of 28713 articles

Human Gait Recognition: A Single Stream Optimal Deep Learning Features Fusion.

Sensors (Basel, Switzerland)
Human Gait Recognition (HGR) is a biometric technique that has been utilized for security purposes for the last decade. The performance of gait recognition can be influenced by various factors such as wearing clothes, carrying a bag, and the walking ...

Research Progress of Gliomas in Machine Learning.

Cells
In the field of gliomas research, the broad availability of genetic and image information originated by computer technologies and the booming of biomedical publications has led to the advent of the big-data era. Machine learning methods were applied ...

Predictive Analysis and Evaluation Model of Chronic Liver Disease Based on BP Neural Network with Improved Ant Colony Algorithm.

Journal of healthcare engineering
Timely prediction of the mechanism and characteristics of chronic liver disease using next-generation information technology is an effective way to improve the diagnosis rate of chronic liver disease. In this paper, we have proposed a modified backpr...

Utilization of Nursing Defect Management Evaluation and Deep Learning in Nursing Process Reengineering Optimization.

Computational and mathematical methods in medicine
It was to explore the application of nursing defect management evaluation and deep learning in nursing process reengineering optimization. This study first selects the root cause analysis method to analyse the nursing defect management, then realizes...

Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches.

Computational and mathematical methods in medicine
A vast amount of data is generated every second for microblogs, content sharing via social media sites, and social networking. Twitter is an essential popular microblog where people voice their opinions about daily issues. Recently, analyzing these o...

Postsurgery Classification of Best-Corrected Visual Acuity Changes Based on Pterygium Characteristics Using the Machine Learning Technique.

TheScientificWorldJournal
INTRODUCTION: Early detection of visual symptoms in pterygium patients is crucial as the progression of the disease can cause visual disruption and contribute to visual impairment. Best-corrected visual acuity (BCVA) and corneal astigmatism influence...

iDHS-DT: Identifying DNase I hypersensitive sites by integrating DNA dinucleotide and trinucleotide information.

Biophysical chemistry
DNase I hypersensitive sites (DHSs) is important for identifying the location of gene regulatory elements, such as promoters, enhancers, silencers, and so on. Thus, it is crucial for discriminating DHSs from non-DHSs. Although some traditional method...

Comparison of time-to-event machine learning models in predicting oral cavity cancer prognosis.

International journal of medical informatics
BACKGROUND: Applying machine learning to predicting oral cavity cancer prognosis is important in selecting candidates for aggressive treatment following diagnosis. However, models proposed so far have only considered cancer survival as discrete rathe...

A Novel Occupancy Mapping Framework for Risk-Aware Path Planning in Unstructured Environments.

Sensors (Basel, Switzerland)
In the context of autonomous robots, one of the most important tasks is to prevent potential damage to the robot during navigation. For this purpose, it is often assumed that one must deal with known probabilistic obstacles, then compute the probabil...

Automatic Multi-Label ECG Classification with Category Imbalance and Cost-Sensitive Thresholding.

Biosensors
Automatic electrocardiogram (ECG) classification is a promising technology for the early screening and follow-up management of cardiovascular diseases. It is, by nature, a multi-label classification task owing to the coexistence of different kinds of...