1,721,004 research outputs found
Exploring radio frequency identification (RFID) in healthcare: Promises fulfilled or forsaken?
No full textNo abstract availabl
Machine Learning Models for Predicting Emotional Valence from Brain Activity and Physiological Responses
No full textIn this study, we developed machine learning models to predict the valence class and valence rating of emotions experienced by participants based on their brain activity and physiological responses. The ICBHI 2024 Scientific Challenge involves using a rich dataset comprising pre-processed functional Magnetic Resonance Imaging (fMRI), photoplethysmography (PPG), and respiratory data from 20 participants. Each participant watched emotion-provoking video clips categorized into three valence classes (positive, negative, neutral) and rated them on a nine-level scale. Our approach integrates Convolutional Neural Networks (CNNs) for analyzing fMRI data and CNNs + Long Short-Term Memory (LSTM) networks for handling PPG and respiratory data. The models were trained to classify the valence class and predict the valence level, using a categorical cross-entropy as loss functions. Initial results show promising trends, indicating the model’s potential for accurate emotion prediction. fMRI model training and validation accuracy are 0.99 and 0.98 respectively. PPG and respiratory models accuracy are 0.86 and 0.66 on training and 0.80 and 0.56 on validation. However, further fine-tuning and architectural adjustments are necessary to enhance performance. This work aims to contribute to understanding how brain activity and physiological responses can be used to decode emotional states, with potential applications in psychological assessment and therapeutic interventions
Decision Support Systems in Healthcare
No full textIn this section, we will describe an example of CDSS that we designed and implemented for facilitating the decision process in the management of the Congestive Heart Failure
An Innovative Solution for Efficient Workflow Management in Healthcare
No full textHospitals are challenged to provide a wider range of services due to a growing patient population, leading to a faster deterioration rate compared to other buildings. Recent years have seen a focus on improving maintenance management in hospitals through strategies, performance measurements, and Information Technology. Challenges include resource allocation, communication gaps, and workflow monitoring. Healthcare workflow management involves various stakeholders and aims to ensure safe, efficient, and effective patient care while minimizing waste and reducing costs. Workflow Management Systems (WFMSs) are promising solutions, automating administrative procedures to enhance efficiency and effectiveness in healthcare services. The paper presents a RESTful WFMS developed in Microsoft .NET 6, utilizing the open-source .NET library Elsa Workflows. It introduces pre-typed sub-workflows, each defined in JSON format, allowing users to customize workflows using Graphic User Interfaces (GUIs). The system stores information in a Microsoft SQL Server database and interacts with the hospital Computer Aided Facility Management (CAFM) system via APIs. The platform enables managers and department heads to create customizable workflows in a no-code environment. The system is used in an actual healthcare environment at the “Le Scotte” University Hospital in Siena, Italy
Computer-aided facilities management in health care
No full textThe complexity of modern hospitals in terms of structural, technological and organizational requirements has been growing exponentially over the years. Hospitals must comply with a large number of requirements in order to fulfill their clinical and medical duties. Computer-Aided Facilities Management Systems have become essential tools to manage such a high level of complexity having a holistic approach. In this chapter, some real-world experiences are shown, by describing some custom tools used every day in the main hospitals in Tuscany
Semantic Ontologies for Complex Healthcare Structures: A Scoping Review
Full text linkThe healthcare environment is made up of highly complicated interactions between many
technologies, activities, and people. Ensuring a solid communication between them is vital to ease the
healthcare management. Semantic ontologies are knowledge representation tools that implement abstractions
to fully describe a given topic in terms of subjects and relations. This scoping review aims to identify
and analyse available ontologies which can depict all the available use-cases that describe the hospital
environment in relation to the European project ODIN and its future expansion. The review has been
conducted on the Scopus database on January 13th, 2023 using the PRISMA extensions for scoping reviews.
Two reviewers screened 3,225 documents emerged from the database search. Further filtering led to a final
set of 32 articles to be analysed for the results. A set of 34 ontologies extracted by the identified articles
has been analysed and discussed as well. The results of this study will lead to the implementation of a
common integrated ontology which could hold information about healthcare entities as well as their semantic
relationships, strengthen data exchange and interconnections among people, devices and applications in an
expanded scenario which include Internet of Things, robots and Artificial Intelligence
Creation of a system for the coding of medical devices
Full text linkMedical devices have different nomenclatures for their classification. Some of the most significant nomenclatures are the Universal Medical Device Nomenclature System (UMDNS) and the Global Medical Device Nomenclature (GMDN) by the Emergency Care Research Institute (ECRI). In Italy the main are CIVAB and “Classificazione Nazionale Dispositivi Medici” (National Classification for Medical Devices - CND). The aim of this study is to create a system to automatically decode several device models from CIVAB to UMDNS code. All medical devices are coded with a table which is based on their definitions presented in these nomenclatures. The coding is lastly applied to a list of models of medical devices, developed by different companies
A Web Based Integrated Healthcare Facility Management System
No full textThis paper presents a custom decision-support information system to analyze and manage healthcare buildings, estate and assets in relation to the carried on activities. The software drives Autocad plans to retrieve structural information and to store any kind of structured data with a room-scale definition. Each room is grouped in homogeneous areas with its own assets, technologies and environmental comforts, giving quantitative and qualitative results. System outputs can be used by the top-management to assess parameters and improve the structure and organization
Assisted Reproductive Technology Center Design with Quality Function Deployment Approach
No full textAssisted Reproductive Technology (ART) is the technology used to achieve pregnancy in procedures such as fertility medication, artificial insemination, in-vitro fertilization and surrogacy. The paper shows an application of Quality Function Deployment method to Careggi Hospital ART Laboratory of Florence in order to give a prioritization order for ameliorative interventions
Enabling reliable usability assessment and comparative analysis of medical software: a comprehensive framework for multimodal biomedical imaging platforms
Full text linkPurpose: A literature review reveals that, at the moment, all usability tests for Software as a Medical Device (SaMD) are designed in compliance with international standards but it also reveals a lack of formalization in the implementation and administration of such usability tests, which prevents the comparison of results from different tests for the same class of SaMD. This study aims to provide a reproducible usability testing framework for SaMD to establish a standardized protocol which can ensure repeatability and comparisons of similar SaMD for the visualization of medical images and data. Methods: The devised protocol aligns with international standards and literature recommendations for usability and human factors engineering. It encompasses participant selection, testing environments, equipment setup for various testing methods (HDMI vs. wireless), and hardware interfaces (keyboard/mouse vs. touchscreen), as well as the roles of the required testers. The protocol consists of two distinct sections: exploratory tasks and specific scenarios, to assess software functions and real-life tasks, respectively. Effectiveness and efficiency are evaluated using video analysis and a custom Stopwatch software, while user satisfaction is measured through post-test questionnaires. Results: The usability testing protocol was applied to a Multimodal Biomedical Imaging Platform All-in-One software developed by Imaginalis S.r.l. (Sesto Fiorentino, Italy) for validation. The results of the usability testing protocol applied to the case-study software demonstrate good values of software’s effectiveness and efficiency, along with user satisfaction supporting the prior heuristic evaluation. The outcomes confirm the robustness, applicability, and reproducibility of the usability testing protocol, aligning with best practices. Conclusions: The proposed usability testing framework enables reliable usability assessment and comparative analysis of medical software. Furthermore, the obtained results can serve as a reference for assessing other biomedical imaging platforms under development or ready for release. © The Author(s) 2024
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