Evidence map›Paper›PMID 29984075›Full record

ArticleBiomedical optics express2018

Quantitative characterization of bovine serum albumin thin-films using terahertz spectroscopy and machine learning methods.

Yiwen Sun, Pengju Du, Xingxing Lu, Pengfei Xie, Zhengfang Qian, Shuting Fan, Zexuan Zhu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical optics express, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

12 citing papers in PubMed, 43 citations in OpenAlex.

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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 at 1 institution in 1 country.

Yiwen SunNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong, Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical, Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Pengju DuNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong, Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical, Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Xingxing LuNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong, Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical, Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Pengfei XieNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong, Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical, Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, China.
Zhengfang QianCollege of Electronic Science and Technology, Shenzhen University, Shenzhen 518060, China.
Shuting FanCollege of Electronic Science and Technology, Shenzhen University, Shenzhen 518060, China.
Zexuan ZhuCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China.
Shenzhen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of new spectral analysis methods in bio thin-film detection has generated intense interest in terahertz (THz) spectroscopy and its application in a wide range of fields. In this paper, it is the first time that machine learning methods are applied to the quantitative characterization of bovine serum albumin (BSA) deposited thin-films detected by terahertz time-domain spectroscopy. The spectra data of BSA thin-films prepared by solutions with concentrations ranging from 0.5 to 35 mg/ml are analyzed using the support vector regression method to learn the underlying model of the frequency against the target concentration. The learned mode successfully predicts the concentrations of the unknown test samples with a coefficient of determination R

Indexed as

(070.4790) Spectrum analysis(170.1420) Biology(300.6495) Spectroscopy, terahertz

Identifiers

PMID29984075
PMCPMC6033555
OpenAlexW2806963097

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.