Evidence map›Paper›PMID 31149379›Full record

ArticleBiomedical optics express2019

Lung cancer diagnosis with quantitative DIC microscopy and a deep convolutional neural network.

Longfei Zheng, Kangyuan Yu, Shuangshuang Cai, Yu Wang, Bixin Zeng, Min Xu

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

Article in Biomedical optics express, 2019. 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
0.7field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 1 institution in 2 countries.

Longfei ZhengInstitute of Lasers and Biomedical Photonics, School of Biomedical Engineering, Wenzhou, Wenzhou Medical University, Wenzhou 325035, China.
Kangyuan YuInstitute of Lasers and Biomedical Photonics, School of Biomedical Engineering, Wenzhou, Wenzhou Medical University, Wenzhou 325035, China.
Shuangshuang CaiInstitute of Lasers and Biomedical Photonics, School of Biomedical Engineering, Wenzhou, Wenzhou Medical University, Wenzhou 325035, China.
Yu WangInstitute of Lasers and Biomedical Photonics, School of Biomedical Engineering, Wenzhou, Wenzhou Medical University, Wenzhou 325035, China.
Bixin ZengInstitute of Lasers and Biomedical Photonics, School of Biomedical Engineering, Wenzhou, Wenzhou Medical University, Wenzhou 325035, China.
Min XuInstitute of Lasers and Biomedical Photonics, School of Biomedical Engineering, Wenzhou, Wenzhou Medical University, Wenzhou 325035, China.
Wenzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a study on lung squamous cell carcinoma diagnosis using quantitative TI-DIC microscopy and a deep convolutional neural network (DCNN). The 2-D phase map of unstained tissue sections is first retrieved from through-focus differential interference contrast (DIC) images based on the transport of intensity equation (TIE). The spatially resolved optical properties are then computed from the 2-D phase map via the scattering-phase theorem. The scattering coefficient (

Identifiers

PMID31149379
PMCPMC6524577
OpenAlexW2937718044

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.