ReviewNPJ digital medicine2026
Current status and future outlook of artificial intelligence and automation in intravenous infusion systems.
Review in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The combination of the Internet of Things (IoT), artificial intelligence (AI), and wearable biosensors is transforming healthcare by allowing continuous, real-time monitoring and more intelligent clinical decision-making. This review explores AI-driven monitoring, smart intravenous (IV) infusion automation, and wearable biosensors, and proposes Intelligent IV Automation and Smart Patient Synchronization (INFUSYNC), a conceptual framework synchronizing monitoring, automated fluid delivery, and predictive analytics. The literature shows meaningful progress: wearables increasingly support non-contact monitoring with near clinical-grade accuracy for select parameters, while infusion pumps with dose-error-reduction and AI-assisted decision support are reported to improve delivery precision and safety. Predictive models further support early detection of physiological decline. Progress remains uneven, however: most AI-enabled infusion systems are prototype-stage, closed-loop control remains rare, and interoperability, data security, and privacy remain underdeveloped. Future systems will need compatible, security-by-design, clinically validated, feedback-controlled architectures. Overall, this review outlines a clear but early-stage trajectory toward integrated smart-health environments for IV therapy.
Identifiers
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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.