ArticleJournal of personalized medicine2019
Omics Meeting Onics: Towards the Next Generation of Spectroscopic-Based Technologies in Personalized Medicine.
Article in Journal of personalized medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- A Brief Review on Medicinal Plants-At-Arms against COVID-19.Interdisciplinary perspectives on infectious diseases · 2023Review
- Novel time-domain NMR-based traits for rapid, label-free Olive oils profiling.NPJ science of food · 2022Article
- Two-dimensional nanostructures based '-onics' and '-omics' in personalized medicine.Nanophotonics (Berlin, Germany) · 2022Review
- Agreement among rapid diagnostic tests, urine malaria tests, and microscopy in malaria diagnosis of adult patients in southwestern Nigeria.The Journal of international medical research · 2022Article
- Review of Microdevices for Hemozoin-Based Malaria Detection.Biosensors · 2022Review
- Multi-Omics Advancements towardsDiagnostics (Basel, Switzerland) · 2021Review
- Visualization and Measurements of Blood Cells Flowing in Microfluidic Systems and Blood Rheology: A Personalized Medicine Perspective.Journal of personalized medicine · 2020Review
- Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy.Communications biology · 2020Article
- Rapid phenotyping towards personalized malaria medicine.Malaria journal · 2020Article
- Molecular phenotyping of oxidative stress in diabetes mellitus with point-of-care NMR system.NPJ aging and mechanisms of disease · 2020Article
- A Perspective on Microneedle-Based Drug Delivery and Diagnostics in Paediatrics.Journal of personalized medicine · 2019Article
- Perspective: Cellular and Molecular Profiling Technologies in Personalized Oncology.Journal of personalized medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This article aims to discuss the recent development of integrated point-of-care spectroscopic-based technologies that are paving the way for the next generation of diagnostic monitoring technologies in personalized medicine. Focusing on the nuclear magnetic resonance (NMR) technologies as the leading example, we discuss the emergence of -onics technologies (e.g., photonics and electronics) and how their coexistence with -omics technologies (e.g., genomics, proteomics, and metabolomics) can potentially change the future technological landscape of personalized medicine. The idea of an open-source (e.g., hardware and software) movement is discussed, and we argue that technology democratization will not only promote the dissemination of knowledge and inspire new applications, but it will also increase the speed of field implementation.
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.