Fine Tuning of an Advanced Planner for Cognitive Training of Older Adults.

Developing effective cognitive training tools for older adults, specifically addressing executive functions such as planning, is a challenging task. It is of paramount importance to ensure the implementation of engaging activities that must be tailored to the specific needs and expectations of older adults. Furthermore, it is essential to provide the appropriate level of complexity for the planning task.

A focus group study for the design of a web-based tool for improving problem-solving in older adults.

The development of easily accessible and usable social and cognitive enhancement trainings is becoming a priority to reduce the impact of aging on quality of life. Since most activities of daily living (e.g.

A Low-Cost Early Warning Method for Infectious Diseases with Asymptomatic Carriers.

At the beginning of 2023, the Italian former prime minister, the former health minister and 17 others including the current president of the Lombardy region were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government's response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse the pandemic data of Italy and the Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020.

Cognitive benefits of the attentional vs exergame training in older adults.

Objective: The present study aimed at comparing the effectiveness of an Attentional Computerized Cognitive Training and a commercial Exergame Training.

Methods: Eighty-four healthy older adults took part in the study. They were randomly assigned to one of the following conditions: Attentional Computerized Cognitive Training (ATT-CCT), Exergame Training (EXERG-T), or passive Control Group (CG).

Predictive Capacity of COVID-19 Test Positivity Rate.

COVID-19 infections can spread silently, due to the simultaneous presence of significant numbers of both critical and asymptomatic to mild cases. While, for the former reliable data are available (in the form of number of hospitalization and/or beds in intensive care units), this is not the case of the latter. Hence, analytical tools designed to generate reliable forecast and future scenarios, should be implemented to help decision-makers to plan ahead (e.

Analysis of news sentiments using natural language processing and deep learning.

This paper investigates if and to what point it is possible to trade on news sentiment and if deep learning (DL), given the current hype on the topic, would be a good tool to do so. DL is built explicitly for dealing with significant amounts of data and performing complex tasks where automatic learning is a necessity. Thanks to its promise to detect complex patterns in a dataset, it may be appealing to those investors that are looking to improve their trading process.

Enhancing cognitive rehabilitation in multiple sclerosis with a disease-specific tool.

Purpose: Computerised rehabilitation programs can be used to address cognitive deficits typically caused by multiple sclerosis (MS). However, there are still doubts on their effectiveness, due to mixed results obtained in clinical trials. The objective of this paper is to improve cognitive rehabilitation (CR) practices in MS, by presenting and assessing a MS-specific cognitive rehabilitation software.

Refining an automatic EDSS scoring expert system for routine clinical use in multiple sclerosis.

The Expanded Disability Status Scale (EDSS) has been the most widely used measure of disability in multiple sclerosis (MS) clinical trials. Although EDSS has the advantage of familiarity with respect to recent proposals, and remains the de facto standard, it is difficult to use consistently between evaluators. Automatic EDSS (AEDSS) is an expert system designed to overcome this problem.

An expert system for the evaluation of EDSS in multiple sclerosis.

Multiple sclerosis is a disease of unknown aetiology. Despite several advances in therapy in recent years, some problems such as the prognostic criteria are imperfectly understood. Several experimental trials of therapy in multiple sclerosis are in course in order to discover a successful treatment.