ArticleBMC medical informatics and decision making2024
KGSCS-a smart care system for elderly with geriatric chronic diseases: a knowledge graph approach.
Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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
7 citing papers in PubMed, 12 citations in OpenAlex.
- A knowledge graph-driven paradigm for holistic symptom management: development and evaluation of a nurse-led KG-QA system in community palliative care.BMC palliative care · 2026Article
- Knowledge graph-enhanced deep learning for pharmaceutical demand forecasting.Scientific reports · 2026Article
- Application scope of knowledge graphs in nursing: a scoping review.Frontiers in public health · 2026Article
- An evidence-weighted knowledge framework with path-aware reasoning for personalized lifestyle management in chronic disease.Frontiers in public health · 2026Article
- Improving the smart care service system for older adults: an emotional experience evaluation framework in the Chinese community.Frontiers in public health · 2025Article
- Developing and evaluating an intelligent integration system for older adult care and health based on the sport-medicine-tourism model.Frontiers in public health · 2025Article
- Coupling coordination evaluation and influencing factors analysis of older adult care service resource supply and demand in China.Frontiers in public health · 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 2 institutions in 1 country.
Funding
Abstract
backgroundThe increasing aging population has led to a shortage of geriatric chronic disease caregiver, resulting in inadequate care for elderly people. In this global context, many older people rely on nonprofessional family care. The credibility of existing health websites cannot meet the needs of care. Specialized health knowledge bases such as SNOMED-CT and UMLS are also difficult for nonprofessionals to use. Furthermore, professional caregiver in elderly care institutions also face difficulty caring for multiple elderly people at the same time and working handovers. As a solution, we propose a smart care system for the elderly based on a knowledge graph.
methodFirst, we worked with professional caregivers to design a structured questionnaire to collect more than 100 pieces of care-related information for the elderly. Then, in the proposed system, personal information, smart device data, medical knowledge, and nursing knowledge are collected and organized into a dynamic knowledge graph. The system offers report generation, question answering, risk identification and data updating services. To evaluate the effectiveness of the system, we use the expert evaluation method to score the user experience.
resultsThe results of the study showed that compared to existing tools (health websites, archives and expert team consultation), the system achieved a score of 8 or more for basic information, health support and Dietary information. Some secondary evaluation indicators reached 9 and 10 points. This finding suggested that the system is superior to existing tools. We also present a case study to help the reader understand the role of the system.
conclusionThe smart care system provide personalized care guidelines for nonprofessional caregivers. It also makes the job easier for institutional caregivers. In addition, the system provides great convenience for work handover.
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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.