A5011113912- Natural Language Processing Techniques
- Topic Modeling
- Family and Patient Care in Intensive Care Units
- Computational Physics and Python Applications
- Text Readability and Simplification
- Fractal and DNA sequence analysis
- Emergency and Acute Care Studies
- Multimodal Machine Learning Applications
- Infant Development and Preterm Care
- Anomaly Detection Techniques and Applications
- Taxation and Legal Issues
- Health and Medical Research Impacts
- Time Series Analysis and Forecasting
- Big Data Technologies and Applications
- Cardiac Arrest and Resuscitation
- Software Engineering Research
- Family and Disability Support Research
- Respiratory Support and Mechanisms
- Geographic Information Systems Studies
- Health Sciences Research and Education
- International Relations and Autism
- Cognitive Science and Mapping
- Human Rights and Immigration
- Innovations in Medical Education
- Radioactive contamination and transfer
Bambino Gesù Children's Hospital
2020-2025
Istituti di Ricovero e Cura a Carattere Scientifico
2025
University of Turin
2019-2021
Agenzia Regionale per la Protezione Ambientale
1998
Abstract Background Early mobilization of adults receiving intensive care improves health outcomes, yet little is known about practices in paediatric units (PICUs). We aimed to determine the prevalence and factors associated with physical rehabilitation PICUs across Europe. Methods A 2-day, cross-sectional, multicentre point study was conducted May November 2018. The primary outcome therapy (PT)- or occupational (OT)-provided mobility. Clinical data on patient mobility, potential mobility...
Abstract Data-to-Text Generation (DTG) is a subfield of Natural Language aiming at transcribing structured data in natural language descriptions. The field has been recently boosted by the use neural-based generators which exhibit on one side great syntactic skills without need hand-crafted pipelines; other side, quality generated text reflects training data, realistic settings only offer imperfectly aligned structure-text pairs. Consequently, state-of-art neural models include misleading...
Abstract Background Involvement in research activities is complex pediatric nursing and allied health professionals (AHPs). It important to understand which individual factors are associated with it inform policy makers promoting research. Methods A cross-sectional observational study was conducted describe the level of participation over last ten years nurses AHPs working a tertiary hospital. large sample an Italian academic hospital completed online self-report questionnaire between June...
In this paper, we analyze the problem of generating fluent English utterances from tabular data, focusing on development a sequence-to-sequence neural model which shows two major features: ability to read and generate character-wise, switch between copying characters input: an essential feature when inputs contain rare words like proper names, telephone numbers, or foreign words. Working with instead is challenge that can bring problems such as increasing difficulty training phase bigger...
Data-to-Text Generation (DTG) is a subfield of Natural Language aiming at transcribing structured data in natural language descriptions. The field has been recently boosted by the use neural-based generators which exhibit on one side great syntactic skills without need hand-crafted pipelines; other side, quality generated text reflects training data, realistic settings only offer imperfectly aligned structure-text pairs. Consequently, state-of-art neural models include misleading statements...
In this paper we present an experiment on digitally-supported collaborative Concept Maps focused asynchronous and remote collaboration.We investigated the integration of multiple perspectives same topic, providing users with a tool allowing individual perspective for each user plus shared one group.Several actions were made available, affecting or both perspectives, depending context.Results show that integrating different in way everyone can relate to is indeed complex task: need be...