ArticleHealthcare (Basel, Switzerland)2022
Similarities and Differences between EU Platforms in the AHA and AAL Domains from a Software Viewpoint.
Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Evaluating a Nationally Localized AI Chatbot for Personalized Primary Care Guidance: Insights from the HomeDOCtor Deployment in Slovenia.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
The EU PlatformUptake project's main goal is to investigate the usage of EU open and partly-open platforms in active and healthy aging (AHA) and ambient-assisted living (AAL) domains, from a software viewpoint. The aim of the project was to provide tools for a deeper interpretation and examination of the platforms, gather user feedback, and use it to improve the state-of-the-art approach in the AHA and AAL domains, and define instructions to enhance the platforms within the recommended order. The emphasis is on the software viewpoint for decision makers. In this paper, we present (i) the PlatformUptake methodology for AHA open platform assessments and its main objectives; (ii) clustering of the analyzed platforms; and (iii) the taxonomies generated from the text descriptions of the chosen platforms. With the use of the clustering tools, we present which platforms could be grouped together due to their similarities. Different numbers of clusters were obtained with two clustering approaches, resulting in the most informative two and four cluster groups. The platforms could be rather neatly presented in this way and, thus, potentially guide future platform structuring. Moreover, taxonomies, i.e., decision trees of platforms, were generated to easily determine each specific platform or to find platforms with the desired properties. Altogether, the computer comprehension of the platforms may be important additions to the human way of dealing with the AHA platforms, influencing future design, publications, related work, and research.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.