Publications by authors named "Aris Anagnostopoulos"
Motivation: Disease gene prioritization consists in identifying genes that are likely to be involved in the mechanisms of a given disease, providing a ranking of such genes. Recently, the research community has used computational methods to uncover unknown gene-disease associations; these methods range from combinatorial to machine learning-based approaches. In particular, during the last years, approaches based on deep learning have provided superior results compared to more traditional ones.
View Article and Find Full Text PDFPublic procurement is viewed as a major market force that can be used to promote innovation and drive small and medium-sized enterprises growth. In such cases, procurement system design relies on intermediates that provide vertical linkages between suppliers and providers of innovative services and products. In this work we propose an innovative methodology for decision support in the process of supplier discovery, which precedes the final supplier selection.
View Article and Find Full Text PDFArticle Synopsis
- Recent research highlights the importance of improving risk stratification for patients with differentiated thyroid cancer (DTC) beyond the existing 2015 American Thyroid Association (ATA) guidelines.
- A study utilizing the Italian Thyroid Cancer Observatory database analyzed 4,773 DTC cases to develop a decision tree model that predicts persistent/recurrent disease by considering a range of predictive factors.
- The new model demonstrated better performance than the ATA guidelines by increasing sensitivity and predictive accuracy, suggesting that incorporating additional variables like age and tumor size can enhance patient risk assessment.
Epidemiological characteristics and outcomes from 187 patients with COVID-19 admitted to 6 reference centers in Greece: an observational study during the first wave of the COVID-19 pandemic.
Adv Respir Med
September 2021
Article Synopsis
- A study conducted in Greece from February to May 2020 analyzed hospitalized COVID-19 patients, revealing that most subjects were male (65.7%) with an average age of 60, predominantly non-smokers (57.2%).
- The majority received a standard treatment regimen including hydroxychloroquine and azithromycin, with an average hospital stay of 10 days; 13.3% required intubation and 4.2% died.
- The findings highlighted that higher neutrophil-to-lymphocyte ratios (NLR) and lactate dehydrogenase (LDH) levels were linked to more severe disease, suggesting these markers may help predict disease progression and inform treatment decisions.
Videos have become a powerful tool for spreading illegal content such as military propaganda, revenge porn, or bullying through social networks. To counter these illegal activities, it has become essential to try new methods to verify the origin of videos from these platforms. However, collecting datasets large enough to train neural networks for this task has become difficult because of the privacy regulations that have been enacted in recent years.
View Article and Find Full Text PDFBackground: Nintedanib represents an antifibrotic compound able to slow down disease progression of patients with idiopathic pulmonary fibrosis (IPF).
Objective: To investigate the safety and efficacy of nintedanib in patients with IPF in a real-life setting.
Methods: This was a multicentre, retrospective, observational, real-life study for patients with IPF receiving nintedanib between October 2014 and October 2016.
Background: Pirfenidone is an antifibrotic compound able to slow down disease progression in patients with idiopathic pulmonary fibrosis (IPF).
Objective: To investigate the safety and efficacy of pirfenidone in patients with IPF in a real-life setting.
Methods: This was a multicenter, retrospective, real-life, observational study for patients with IPF receiving pirfenidone.