6 results match your criteria: "Center for Digital Health and Wellbeing[Affiliation]"
Human centered design of AI-powered Digital Therapeutics for stress prevention: Perspectives from multi-stakeholders' workshops about the SHIVA solution.
Internet Interv
December 2024
Digital Health Research, Center for Digital Health and Wellbeing, Fondazione Bruno Kessler, Trento, Italy.
Background: AI-powered Digital Therapeutics (DTx) hold potential for enhancing stress prevention by promoting the scalability of P5 Medicine, which may offer users coping skills and improved self-management of mental wellbeing. However, adoption rates remain low, often due to insufficient user and stakeholder involvement during the design phases.
Objective: This study explores the human-centered design potentials of SHIVA, a DTx integrating virtual reality and AI with the SelfHelp+ intervention, aiming to understand stakeholder views and expectations that could influence its adoption.
Toward a digitalized medicine: the Covid-19 pandemic as a disclosure of the importance of digital communication in the clinical world.
Theor Med Bioeth
June 2024
Intelligent Digital Agents Unit (IDA)-Center for Digital Health and Wellbeing, Fondazione Bruno Kessler, Trento, Italy.
This paper focuses on the importance of digital communication between medical teams and patients and their families when mediated by technological tools. Medicine is changing following the fourth industrial (the digital) revolution: from CAT scans, to X-rays, to UV radiation, to electronic records, to treatment tracking apps, to telemedicine, and the use of AI in doctors' decision-making processes. The COVID-19 pandemic highlighted both the fruitful and problematic sides of this medical evolution.
View Article and Find Full Text PDFCommunication, understanding and engagement of patients with pancreatic cancer at time of diagnosis.
Pancreatology
May 2024
Pancreato-Biliary Endoscopy and Endosonography Unit, Pancreas Translational & Clinical Research Center, San Raffaele Scientific Institute IRCCS, Via Olgettina, 58, 20132, Milan, Italy; Vita-Salute San Raffaele University, Via Olgettina, 58, 20132, Milan, Italy. Electronic address:
Article Synopsis
- The study examined how clear communication during the diagnosis of pancreatic adenocarcinoma (PDAC) affects patient engagement and adherence to treatment.
- Researchers enrolled 30 patients and found a high engagement level, with 70% actively participating and nearly all patients compliant with treatment, though many experienced misunderstandings during discussions about their diagnosis and treatment.
- Key findings highlighted the dynamics of doctor-patient conversations, showing that doctors spoke significantly more than patients or caregivers, and that regional background influenced engagement levels, necessitating further research into communication improvements.
Exploring the Latest Highlights in Medical Natural Language Processing across Multiple Languages: A Survey.
Yearb Med Inform
August 2023
Natural Language Processing Research Unit, Center for Digital Health and Wellbeing, Fondazione Bruno Kessler, Trento, Italy.
Objectives: This survey aims to provide an overview of the current state of biomedical and clinical Natural Language Processing (NLP) research and practice in Languages other than English (LoE). We pay special attention to data resources, language models, and popular NLP downstream tasks.
Methods: We explore the literature on clinical and biomedical NLP from the years 2020-2022, focusing on the challenges of multilinguality and LoE.
Discovering functional connectivity features characterizing multiple sclerosis phenotypes using explainable artificial intelligence.
Hum Brain Mapp
April 2023
Pattern Analysis and Computer Vision, Istituto Italiano di Tecnologia, Genova, Italy.
Article Synopsis
- Multiple sclerosis (MS) is a neurological condition that leads to severe brain damage and changes in brain function, with variations in these effects depending on the MS phase.
- The study discusses a machine learning system that analyzes resting-state functional connectivity (RS FC) data to differentiate between various MS phenotypes and pinpoint crucial functional connections for identifying disease stages.
- The framework demonstrated strong classification performance across all MS types and effectively identified significant RS FC changes that aid in accurate phenotype classification.
Investigating the spectral features of the brain meso-scale structure at rest.
Hum Brain Mapp
October 2021
Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genova, Italy.
Recent studies provide novel insights into the meso-scale organization of the brain, highlighting the co-occurrence of different structures: classic assortative (modular), disassortative, and core-periphery. However, the spectral properties of the brain meso-scale remain mostly unexplored. To fill this knowledge gap, we investigated how the meso-scale structure is organized across the frequency domain.
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