AIMC Topic: Machine Learning

Clear Filters Showing 15571 to 15580 of 34417 articles

Application of artificial intelligence techniques for automated detection of myocardial infarction: a review.

Physiological measurement
Myocardial infarction (MI) results in heart muscle injury due to receiving insufficient blood flow. MI is the most common cause of mortality in middle-aged and elderly individuals worldwide. To diagnose MI, clinicians need to interpret electrocardiog...

Multi-Task Weakly-Supervised Attention Network for Dementia Status Estimation With Structural MRI.

IEEE transactions on neural networks and learning systems
Accurate prediction of clinical scores (of neuropsychological tests) based on noninvasive structural magnetic resonance imaging (MRI) helps understand the pathological stage of dementia (e.g., Alzheimer's disease (AD)) and forecast its progression. E...

Global Negative Correlation Learning: A Unified Framework for Global Optimization of Ensemble Models.

IEEE transactions on neural networks and learning systems
Ensembles are a widely implemented approach in the machine learning community and their success is traditionally attributed to the diversity within the ensemble. Most of these approaches foster diversity in the ensemble by data sampling or by modifyi...

A Plug-in Method for Representation Factorization in Connectionist Models.

IEEE transactions on neural networks and learning systems
In this article, we focus on decomposing latent representations in generative adversarial networks or learned feature representations in deep autoencoders into semantically controllable factors in a semisupervised manner, without modifying the origin...

Optimizing Attention for Sequence Modeling via Reinforcement Learning.

IEEE transactions on neural networks and learning systems
Attention has been shown highly effective for modeling sequences, capturing the more informative parts in learning a deep representation. However, recent studies show that the attention values do not always coincide with intuition in tasks, such as m...

Link Prediction Based on Stochastic Information Diffusion.

IEEE transactions on neural networks and learning systems
Link prediction (LP) in networks aims at determining future interactions among elements; it is a critical machine-learning tool in different domains, ranging from genomics to social networks to marketing, especially in e-commerce recommender systems....

Automatic analysis system for abnormal red blood cells in peripheral blood smears.

Microscopy research and technique
The type and ratio of abnormal red blood cells (RBCs) in blood can be identified through peripheral blood smear test. Accurate classification is important because the accompanying diseases indicated by abnormal RBCs vary. In clinical practice, this t...

Android Spyware Detection Using Machine Learning: A Novel Dataset.

Sensors (Basel, Switzerland)
Smartphones are an essential part of all aspects of our lives. Socially, politically, and commercially, there is almost complete reliance on smartphones as a communication tool, a source of information, and for entertainment. Rapid developments in th...

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.

JMIR mHealth and uHealth
BACKGROUND: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can hel...

New feature extraction from phylogenetic profiles improved the performance of pathogen-host interactions.

Frontiers in cellular and infection microbiology
MOTIVATION: The understanding of pathogen-host interactions (PHIs) is essential and challenging research because this potentially provides the mechanism of molecular interactions between different organisms. The experimental exploration of PHI is tim...