Evidence map›Paper›PMID 36140069›Full record

ArticleBiosensors2022

A Detection-Service-Mobile Three-Terminal Software Platform for Point-of-Care Infectious Disease Detection System.

Xiangyi Su, Yile Fang, Haoran Liu, Yue Wang, Minjie Ji, Zhu Chen, Hui Chen, Song Li, Yan Deng, Lian Jin and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Xiangyi SuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Yile FangState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Haoran LiuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Yue WangState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Minjie JiState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Zhu ChenHunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China.
Hui ChenHunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China.
Song LiHunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China.
Yan DengHunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China.
Lian JinHunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China.
Yuanying ZhangDepartment of Molecular Biology, Jiangsu Cancer Hospital, Nanjing 210009, China.
Murugan RamalingamInstitute of Tissue Regeneration Engineering, Department of Nanobiomedical Science, BK21 NBM Global Research Center for Regenerative Medicine, Dankook University, Cheonan 31116, Korea.ORCID 0000-0001-6498-9792
Nongyue HeState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.

Funding

Hunan Key R & D Projects 2021SK2003Hunan Urgency Project 2020SK3005National Natural Science Foundation of China 62071119 and 81902153State Key Laboratory of Oral Diseases SKLOD2022OF05
6 · The paper itself

Abstract

The traditional infectious disease detection process is cumbersome, and there is only a single application scenario. In recent years, with the development of the medical industry and the impact of the epidemic situation, the number of infectious disease detection instruments based on nursing point detection has been increasing. Due to this trend, many detection instruments and massive detection data urgently need to be managed. In addition, the experiment failed due to the abnormal fluorescence curve generated by a human operator or sample impurities. Finally, the geographic information system has also played an active role in spreading and preventing infectious diseases; this paper designs a "detection-service-mobile" three-terminal system to realize the control of diagnostic instruments and the comprehensive management of data. Machine learning is used to classify the enlarged curve and calculate the cycle threshold of the positive curve; combined with a geographic information system, the detection results are marked on the mobile terminal map to realize the visual display of the positive results of nucleic acid amplification detection and the early warning of infectious diseases. In the research, applying this system to portable field pathogen detection is feasible and practical.

Indexed as

Communicable DiseasesNucleic AcidsHumansNucleic Acid Amplification TechniquesPoint-of-Care SystemsSoftwareNucleic Acidsgeographic information systeminfectious disease warningmachine learningpoint-of-care testingthree-terminal software

Identifiers

PMID36140069
PMCPMC9496057

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.