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Airsense-to-act: A concept paper for covid-19 countermeasures based on artificial intelligence algorithms and multi-source data processing
Get PDFThe aim of this concept paper is the description of a new tool to support institutions in the implementation of targeted countermeasures, based on quantitative and multi-scale elements, for the fight and prevention of emergencies, such as the current COVID-19 pandemic. The tool is a cloud-based centralized system; a multi-user platform that relies on artificial intelligence (AI) algorithms for the processing of heterogeneous data, which can produce as an output the level of risk. The model includes a specific neural network which is first trained to learn the correlations between selected inputs, related to the case of interest: environmental variables (chemical–physical, such as meteorological), human activity (such as traffic and crowding), level of pollution (in particular the concentration of particulate matter) and epidemiological variables related to the evolution of the contagion. The tool realized in the first phase of the project will serve later both as a decision support system (DSS) with predictive capacity, when fed by the actual measured data, and as a simulation bench performing the tuning of certain input values, to identify which of them led to a decrease in the degree of risk. In this way, we aimed to design different scenarios to compare different restrictive strategies and the actual expected benefits, to adopt measures sized to the actual needs, adapted to the specific areas of analysis and useful for safeguarding human health; and we compared the economic and social impacts of the choices. Although ours is a concept paper, some preliminary analyses have been shown, and two different case studies are presented, whose results have highlighted a correlation between NO2, mobility and COVID-19 data. However, given the complexity of the virus diffusion mechanism, linked to air pollutants but also to many other factors, these preliminary studies confirmed the need, on the one hand, to carry out more in-depth analyses, and on the other, to use AI algorithms to capture the hidden relationships among the huge amounts of data to process
A Decision Support System Based on Machine Learning to Counteract Covid-Like Pandemic Events
No full textIn this paper, the authors aim to design a decision support system (DSS) based on machine learning (ML) to assist institutions in implementing targeted countermeasures to combat and prevent emergencies such as the COVID -19 pandemic. The DSS relies on an ensemble of several ML models that combine heterogeneous data to predict risk levels at the micro and macro levels. Some preliminary analyses have already been conducted showing the correlation between nitrogen dioxide (NO2), mobility-related parameters, and COVID -19 data. However, given the complexity of the virus spread mechanism, which is related to many different factors, these preliminary studies confirmed the need to perform more in-depth analyses on the one hand and to use ML algorithms on the other hand to capture the hidden relationships between the huge amounts of data that need to be processed
Non-muscle invasive urothelial bladder cancer (NMIBC) in very elderly patients: What does affect overall survival (OS)? Clinical outcomes in a retrospective analysis
No full textIntroduction & Objectives: Non-muscle invasive urothelial bladder cancer (NMIBC) represents a common neoplasm in patients older than 75 years old. Our aim was to analyze retrospectively the population of patients (pts) older than 85 years old treated at our department for bladder tumor. Primary outcome measures were the evaluation of overall survival (OS) and recurrence related to clinical-pathological features. Secondary outcome measures were the evaluation of any relation between treatmeants and OS.
Materials & Methods: We looked retrospectively at 118 patients aged 85 years old or more who underwent transurethral resection (TURBT) for bladder tumor (BT) in our hospital between 2001 and 2015.
We registered pre-operative clinical-pathological features and clinical outcomes. Statistical analysis was performed by SPSS.
Results: A total of 47 females (39.8%) and 71 males (60.2%) with an a mean age of 88.13 (SD +/- 3.17) and mean ASA score 2.55 (+/- 0.5) were included in this study; 91 pts died (77.1%)
and 27 (22.9%) are alive. Median time-to-death was 13.5 months (IQR 2-34) and median disease free survival (DFS) was 8 months (IQR 0-24). At diagnosis 28 pts already had
advanced disease (23.72%). 4 pts underwent radical cistectomy (RC), 2 had partial cistectomy, 1 had radiotherapy for palliation and 110 had no further radical treatments (93.22%).
Histotype was urothelial in 99 pts (83.89%), squamoid in 9 patients (7.62%) and undifferentiated in 10 cases (8.47%). 92 pts had no intravescical therapy (77.96%); 19 had BCG
(16.1%) and 7 had MMC (5.93%). 79 pts had low grade (LG) disease (66.94%), 38 had high grade (HG) disease (32.20%) and 1 patient had CIS (0.84%). Among pts with HG disease 7
survived (18.4%) and 31 died (81.6%); among those with LG disease 20 survived (25.3%) and 59 died (74.7%). Among pts who received an intravescical treatment 33.33% survived;
among those who did not received it 19.57% survived. Total recurrence rate was 38.14%.
Conclusions: Bladder cancer is a well-known disease with an high rate of morbidity and mortality. In our series, HG grade disease, was not associated with higher mortality rate (81.6% vs 74,7%
p=0.157) nor with recurrence rate (p=0.452). Tumor size and histotype seemed to be related to recurrence (p=0.001 and p=0.009 respectively). Intravescical treatment did not
seemed to improve OS (p=0.06). Men seemed to have higher risk of recurrence (47.8% vs 23.4%, p=0.006). In the whole population recurrence seemed to not affect overall survival
(p=0.72). Our study seems to demonstrate that clinico-pathological features of BT does not affect OS in very elderly pts. Further studies in larger cohorts of pts maybe needed
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Intraoperative ultrasound in robot-assisted partial nephrectomy: State of the art
Get PDFIntroduction: Nephron-sparing surgery (NSS) is of one of the most studied fields in urology due to the balancing between renal function preservation and oncological safety of the procedure. Aim of this short review is to report the state of the art of intra-operative ultrasound as an operative tool to improve localization of small renal masses partially or completely endophytic during robot-assisted partial nephrectomy (RAPN). Material and methods: We performed a literature review by electronic database on Pubmed about the use of intra-operative US in RAPN to evaluate the usefulness and the feasibility of this procedure. Results: Several studies analyzed the use of different US probes during RAPN. Among them some focused on using contrast-enhanced ultra sonography (CEUS) for improving the dynamic evaluation of microvascular structure allowing the reduction of ischemia time (IT). We reported that nowaday the use of intraoperative US during RAPN could be helpful to improve the preservation of renal tissue without compromising oncological safety. Moreover, during RAPN there is no need for assistant to hand the US probe increasing surgeon autonomy. Conclusions: The use of a robotic ultrasound probe during partial nephrectomy allows the surgeon to optimize tumor identification with maximal autonomy, and to benefit from the precision and articulation of the robotic instrument during this key step of the partial nephrectomy procedure. Moreover US could be useful to reduce ischemia time (IT). The advantages of nephron-sparing surgery over radical nephrectomy is well established with a pool of data providing strong evidence of oncological and survival equivalency. With the progressive growth of robot-assisted partial nephrectomy (RAPN) techniques, the use of several tools has been progressively developed to help the surgeon in the identification of masses and its vascular net. In this short review we tried to analyze the current use of intra-operative ultrasound as an operative tool to improve localization of small renal masses partially or completely endophytic during RAPN
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