Neural networks : the official journal of the International Neural Network Society
Sep 9, 2023
Twin support vector machine (TSVM) is a practical machine learning algorithm, whereas traditional TSVM can be limited for data with outliers or noises. To address this problem, we propose a novel TSVM with the symmetric LINEX loss function (SLTSVM) f...
Neural networks : the official journal of the International Neural Network Society
Sep 9, 2023
Much mathematical effort has been devoted to developing Principal Component Analysis (PCA), which is the most popular feature extraction method. To suppress the negative effect of noise on PCA performance, there have been extensive studies and applic...
Neural networks : the official journal of the International Neural Network Society
Sep 9, 2023
In this paper, we investigate the problem of causal image classification with multi-label learning. As multi-label learning involves a diversity of supervision signals, it is considered a challenging issue to solve. Previous approaches have attempted...
Methods (San Diego, Calif.)
Sep 9, 2023
Heart rate variability (HRV) is an important indicator of autonomic nervous system activity and can be used for the identification of affective states. The development of remote Photoplethysmography (rPPG) technology has made it possible to measure p...
BMC medical informatics and decision making
Sep 9, 2023
BACKGROUND: Food frequency questionnaires (FFQs) are one of the most useful tools for studying and understanding diet-disease relationships. However, because FFQs are self-reported data, they are susceptible to response bias, social desirability bias...
Aging clinical and experimental research
Sep 8, 2023
The increasing access to health data worldwide is driving a resurgence in machine learning research, including data-hungry deep learning algorithms. More computationally efficient algorithms now offer unique opportunities to enhance diagnosis, risk s...
ACS synthetic biology
Sep 8, 2023
Knowledge mining from synthetic biology journal articles for machine learning (ML) applications is a labor-intensive process. The development of natural language processing (NLP) tools, such as GPT-4, can accelerate the extraction of published inform...
Journal of chemical information and modeling
Sep 8, 2023
New solid-state materials have been discovered using various approaches from atom substitution in density functional theory (DFT) to generative models in machine learning. Recently, generative models have shown promising performance in finding new ma...
PloS one
Sep 8, 2023
With the advances in technology and data science, machine learning (ML) is being rapidly adopted by the health care sector. However, there is a lack of literature addressing the health conditions targeted by the ML prediction models within primary he...
Journal of chemical information and modeling
Sep 7, 2023
The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug design; it is considered as a promising solution for assessing the safety profile of compounds, particu...