ReviewSensors (Basel, Switzerland)2022
Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review.
Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 31 citations in OpenAlex.
- SARS-CoV-2 Point-of-Care Testing Modalities: Integrating Molecular, Immunological, Biosensor, and AI Approaches.Diagnostics (Basel, Switzerland) · 2026Review
- A new era in identification of tick genera; artificial intelligence for precision and speed.PeerJ. Computer science · 2026Article
- I-BrainNet: Deep Learning and Internet of Things (DL/IoT)-Based Framework for the Classification of Brain Tumor.Journal of imaging informatics in medicine · 2025Article
- Deep Learning-Enhanced Nanozyme-Based Biosensors for Next-Generation Medical Diagnostics.Biosensors · 2025Review
- Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review.Diagnostics (Basel, Switzerland) · 2025Review
- IoMT Architecture for Fully Automated Point-of-Care Molecular Diagnostic Device.Sensors (Basel, Switzerland) · 2025Article
- A label-free nanowell-based impedance sensor for ten-minute SARS-CoV-2 detection.Sensors & diagnostics · 2025Article
- Golden insights for exploring cancer: delivery, from genes to the human body using bimetallic Au/Ag nanostructures.Discover oncology · 2025Review
- I-Brainer: Artificial intelligence/Internet of Things (AI/IoT)-Powered Detection of Brain CancerCurrent medical imaging · 2025Article
- Expert consensus on One Health for establishing an enhanced and integrated surveillance system for key infectious diseases.Infectious medicine · 2024Article
- Smartphone-based device for point-of-care diagnostics of pulmonary inflammation using convolutional neural networks (CNNs).Scientific reports · 2024Article
- An Optimized Model Based on Deep Learning and Gated Recurrent Unit for COVID-19 Death Prediction.Biomimetics (Basel, Switzerland) · 2023Article
- COVID-19 Severity Prediction from Chest X-ray Images Using an Anatomy-Aware Deep Learning Model.Journal of digital imaging · 2023Article
- The Application of Deep Learning for the Segmentation and Classification of Coronary Arteries.Diagnostics (Basel, Switzerland) · 2023Article
- Smart Graphene-Based Electrochemical Nanobiosensor for Clinical Diagnosis: Review.Sensors (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen-antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.
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.