Evidence map›Paper›PMID 40771575›Full record

ReviewResearch (Washington, D.C.)2024

Challenges and Prospects of Personalized Healthcare Based on Surface-Enhanced Raman Spectroscopy.

Guoqun Li, Xingce Fan, Xiao Tang, Xing Zhao, Qi Hao, Jiaqi Li, Teng Qiu

Abstract readReview
In one paragraph

Review in Research (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Guoqun LiKey Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing 211189, China.
Xingce FanKey Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing 211189, China.
Xiao TangKey Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing 211189, China.
Xing ZhaoKey Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing 211189, China.
Qi HaoKey Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing 211189, China.
Jiaqi LiKey Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing 211189, China.
Teng QiuKey Laboratory of Quantum Materials and Devices of Ministry of Education, School of Physics, Southeast University, Nanjing 211189, China.ORCID https://orcid.org/0000-0002-1160-2619

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalized healthcare monitoring is a transformative tool for preventing potential risks and enhancing health status, particularly through molecular-level insights. Advances in nanotechnology, smart devices, and artificial intelligence (AI) have revolutionized personalized healthcare, especially in point-of-care testing (POCT), enabling early detection and timely intervention. Recently, surface-enhanced Raman spectroscopy (SERS) technology, particularly with flexible chips, has shown immense promise in this field due to its in situ, rapid, specific, and efficient detection capabilities. In this review, we highlight recent advancements in flexible SERS chips for personalized healthcare monitoring, demonstrating their effectiveness in target sampling and detection. Importantly, we provide a comprehensive overview of potential applications of flexible SERS chips in personalized healthcare, address current challenges, and propose future development directions. We also explore the future development of miniaturized Raman devices to broaden their applications in personalized healthcare monitoring. Additionally, we underscore the important role of AI in enhancing data processing and analysis. Our aim is to offer a thorough guide on integrating SERS into personalized healthcare monitoring, promising a new era of health management.

Identifiers

PMID40771575
PMCPMC12327435

What OpenQuestion holds

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Registered trials

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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.