ReviewSensors (Basel, Switzerland)2025
Optimizing Spectral Utilization in Healthcare Internet of Things.
Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- A translational IoT healthcare framework integrating secure sensing, energy-aware intelligence, and adaptive emergency response.Scientific reports · 2026Article
- Energy-Aware Ultra-Reliable Low-Latency Communication for Healthcare IoT in Beyond 5G and 6G Networks.Sensors (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
4 authors.
Funding
Abstract
The mainstream adoption of Internet of Things (IoT) devices for health and lifestyle tracking has revolutionized health monitoring systems. Sixth-generation (6G) cellular networks enable IoT healthcare services to reduce the pressures on already resource-constrained facilities, leveraging enhanced ultra-reliable low-latency communication (eURLLC) to make sure critical health data are transmitted with minimal delay. Any delay or information loss can result in serious consequences, making spectrum availability a crucial bottleneck. This study systematically identifies challenges in optimizing spectrum utilization in healthcare IoT (H-IoT) networks, focusing on issues such as dynamic spectrum allocation, interference management, and prioritization of critical medical devices. To address these challenges, the paper highlights emerging solutions, including artificial intelligence-based spectrum management, edge computing integration, and advanced network architectures such as massive multiple-input multiple-output (mMIMO) and terahertz (THz) communication. We identify gaps in the existing methodologies and provide potential research directions to enhance the efficiency and reliability of eURLLC in healthcare environments. These findings offer a roadmap for future advancements in H-IoT systems and form the basis of our recommendations, emphasizing the importance of tailored solutions for spectrum management in the 6G era.
Indexed as
Identifiers
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.