Evidence map›Paper›PMID 35200308›Full record

ArticleBiosensors2022

Field-Portable Leukocyte Classification Device Based on Lens-Free Shadow Imaging Technique.

Dongmin Seo, Euijin Han, Samir Kumar, Eekhyoung Jeon, Myung-Hyun Nam, Hyun Sik Jun, Sungkyu Seo

Open access · goldAbstract read
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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 21% 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

5 citing papers in PubMed, 18 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.

Dongmin SeoDepartment of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.
Euijin HanDepartment of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.
Samir KumarDepartment of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.ORCID 0000-0002-6302-6326
Eekhyoung JeonDepartment of Biotechnology and Bioinformatics, Korea University, Sejong 30019, Korea.
Myung-Hyun NamDepartment of Laboratory Medicine, College of Medicine, Korea University Anam Hospital, Seoul 02841, Korea.ORCID 0000-0002-8737-6902
Hyun Sik JunDepartment of Biotechnology and Bioinformatics, Korea University, Sejong 30019, Korea.
Sungkyu SeoDepartment of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.ORCID 0000-0001-7990-7390
Korea University · KR

Funding

Korea Medical Device Development Fund Project#: 202012E04Ministry of Oceans and Fisheries 'Development of Management Technology for HNS Accident' and 'Development of Technology for Impact Assessment and Management of HNS discharged from Marine Industrial Facilities'National Research Foundation of Korea Grant#: 2014R1A6A1030732, Grant#: 2020R1A2C1012109
6 · The paper itself

Abstract

The complete blood count (CBC) is one of the most important clinical steps in clinical diagnosis. The instruments used for CBC are usually expensive and bulky and require well-trained operators. Therefore, it is difficult for medical institutions below the tertiary level to provide these instruments, especially in underprivileged countries. Several reported on-chip blood cell tests are still in their infancy and do not deviate from conventional microscopic or impedance measurement methods. In this study, we (i) combined magnetically activated cell sorting and the differential density method to develop a method to selectively isolate three types of leukocytes from blood and obtain samples with high purity and concentration for portable leukocyte classification using the lens-free shadow imaging technique (LSIT), and (ii) established several shadow parameters to identify the type of leukocytes in a complete leukocyte shadow image by shadow image analysis. The purity of the separated leukocytes was confirmed by flow cytometry. Several shadow parameters such as the "order ratio" and "minimum ratio" were developed to classify the three types of leukocytes. A shadow image library corresponding to each type of leukocyte was created from the tested samples. Compared with clinical reference data, a correlation index of 0.98 was obtained with an average error of 6% and a confidence level of 95%. This technique offers great potential for biological, pharmaceutical, environmental, and clinical applications, especially where point-of-care detection of rare cells is required.

Indexed as

Image Processing, Computer-AssistedLeukocytesFlow Cytometryblood cell classificationCMOS image sensordiagnosticslens-free shadow imaging technique (LSIT)leukocytes

Identifiers

PMID35200308
PMCPMC8869521
OpenAlexW4206692313

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.