A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the Internet of Things (IoT). Several different machine learning algorithms exploit the patterns extract...
Non-obstructive azoospermia (NOA) is among the most severe factors for male infertility, but our understandings of the latent biological mechanisms remain insufficient. The single-cell RNA sequencing (scRNA-seq) data of 432 testicular cells isolated ...
Artificial Intelligence and machine learning (ML) methods are promising for risk-stratification, but the added benefit over traditional statistical methods remains unclear. We compared predictive models developed using machine learning (ML) methods t...
Ulcerative colitis (UC) is an immune-related disorder with enhanced prevalence globally. Early diagnosis is critical for the effective treatment of UC. However, it still lacks specific diagnostic signatures. The aim of our study was to explore effici...
Cervical cancer is still one of the most common gynecologic cancers in the world. Since cervical cancer is a potentially preventive cancer, earlier detection is the most effective technique for decreasing the worldwide incidence of the illness. Thi...
IEEE transactions on pattern analysis and machine intelligence
Nov 3, 2021
This paper analyzes regularization terms proposed recently for improving the adversarial robustness of deep neural networks (DNNs), from a theoretical point of view. Specifically, we study possible connections between several effective methods, inclu...
The Internet's popularization has increased the amount of content produced and consumed on the web. To take advantage of this new market, major content producers such as Netflix and Amazon Prime have emerged, focusing on video streaming services. How...
International journal of environmental research and public health
Nov 3, 2021
In many related works, nominal classification algorithms ignore the order between injury severity levels and make sub-optimal predictions. Existing ordinal classification methods suffer rank inconsistency and rank non-monotonicity. The aim of this pa...
This study investigated the effectiveness of pre-treatment quantitative MRI and clinical features along with machine learning techniques to predict local failure in patients with brain metastasis treated with hypo-fractionated stereotactic radiation ...
BACKGROUND: Assessing patient-reported outcomes (PROs) through interviews or conversations during clinical encounters provides insightful information about survivorship.
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