Publications by authors named "Anna Monreale"
Article Synopsis
- - The study investigates the relationship between various lifestyle exposures (the exposome) and genetic factors in the risk of developing pancreatic ductal adenocarcinoma (PDAC), using a large case-control analysis from the UK Biobank.
- - Researchers identified 52 significant associations with PDAC risk, reaffirming known factors like smoking and obesity, while also discovering potential links between mobile phone use, stress, and the disease.
- - Despite the connection between genetic predisposition and PDAC risk, the study found no significant interactions between genetic and environmental factors, suggesting that lifestyle choices may have a more substantial impact on risk.
Article Synopsis
- - The study explores how local environmental factors, such as air quality and proximity to the coast, potentially influence cancer susceptibility, particularly focusing on prostate cancer and its relationship with physical activity and outdoor time.
- - Using data from the UK Biobank, researchers analyzed 12 environmental exposures and their associations with various cancers in a large cohort, revealing 36 significant links and suggesting that individuals living farther from the coast had an increased risk of prostate cancer.
- - Findings indicate that while genetic factors do play a role, local environmental factors and genetic variability contribute to cancer risk independently, highlighting the complex interplay between our surroundings and genetics in cancer development.
Occlusion-Based Explanations in Deep Recurrent Models for Biomedical Signals.
Entropy (Basel)
August 2021
The biomedical field is characterized by an ever-increasing production of sequential data, which often come in the form of biosignals capturing the time-evolution of physiological processes, such as blood pressure and brain activity. This has motivated a large body of research dealing with the development of machine learning techniques for the predictive analysis of such biosignals. Unfortunately, in high-stakes decision making, such as clinical diagnosis, the opacity of machine learning models becomes a crucial aspect to be addressed in order to increase the trust and adoption of AI technology.
View Article and Find Full Text PDFThe rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the "phase 2" of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens' privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking.
View Article and Find Full Text PDFBackground: Gastroesophageal reflux disease (GERD) is one of the most common gastrointestinal disorders worldwide, with relevant impact on the quality of life and health care costs.The aim of our study is to assess the prevalence of GERD based on self-reported symptoms among university students in central Italy. The secondary aim is to evaluate lifestyle correlates, particularly eating habits, in GERD students using automatically recorded transactions through cashiers at university canteen.
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