Publications by authors named "D Zambon"
Article Synopsis
- - The article explores the connection between cholesterol levels and Alzheimer's disease, noting early observations of brain amyloid accumulation in those who died from heart attacks and how high cholesterol may accelerate this process.
- - Research indicates that cholesterol-lowering treatments could potentially reduce amyloid buildup, with evidence suggesting that managing cholesterol in midlife may lower Alzheimer's risk, especially in individuals aged 40 to 55.
- - While observational studies hint at a protective effect of statins against Alzheimer's, clinical trials show mixed results due to factors like timing, type of statin, and patient selection, leading to a call for exploring alternative treatment targets in cholesterol-related Alzheimer's research.
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection.
IEEE Trans Pattern Anal Mach Intell
December 2024
Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series analytics is therefore crucial to unlocking the wealth of information implicit in available data. With the recent advancements in graph neural networks (GNNs), there has been a surge in GNN-based approaches for time series analysis.
View Article and Find Full Text PDFBackground: Available studies suggest that bone marrow concentrate, highly enriched in mesenchymal stem cells, is a potentially encouraging treatment for knee osteoarthritis. The aim of this retrospective study was to evaluate the clinical outcome in patients affected by this condition after treatment with autologous bone marrow aspirate concentrate (BMAC).
Methods: 55 patients who had undergone a single intra-articular injection of BMAC were administered two questionnaires to clinically evaluate their condition based on patient-reported outcome measures before treatment and at follow-up.
Article Synopsis
- * Out of 696 patients studied, a high persistence rate of 96.1% with PCSK9i treatment was observed over a median follow-up of 3.7 years, leading to significant reductions in LDL-C levels.
- * The treatment not only improved cholesterol management, with 77% reaching 2016 LDL-C goals, but also maintained a good quality of life for the patients throughout the study period.
Many recent works in the field of graph machine learning have introduced pooling operators to reduce the size of graphs. In this article, we present an operational framework to unify this vast and diverse literature by describing pooling operators as the combination of three functions: selection, reduction, and connection (SRC). We then introduce a taxonomy of pooling operators, based on some of their key characteristics and implementation differences under the SRC framework.
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