Evidence map›Paper›PMID 38247948›Full record

ArticleBioengineering (Basel, Switzerland)2024

U-Net Convolutional Neural Network for Real-Time Prediction of the Number of Cultured Corneal Endothelial Cells for Cellular Therapy.

Naoki Okumura, Takeru Nishikawa, Chiaki Imafuku, Yuki Matsuoka, Yuna Miyawaki, Shinichi Kadowaki, Makiko Nakahara, Yasushi Matsuoka, Noriko Koizumi

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

Article in Bioengineering (Basel, Switzerland), 2024. 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
1.6field-weighted citation impact, top 18% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

9 authors at 1 institution in 1 country.

Naoki OkumuraDepartment of Biomedical Engineering, Faculty of Life and Medical Sciences, Doshisha University, 1-3 Miyakodani, Tatara, Kyotanabe-City 610-0394, Kyoto, Japan.
Takeru NishikawaDepartment of Biomedical Engineering, Faculty of Life and Medical Sciences, Doshisha University, 1-3 Miyakodani, Tatara, Kyotanabe-City 610-0394, Kyoto, Japan.
Chiaki ImafukuDepartment of Biomedical Engineering, Faculty of Life and Medical Sciences, Doshisha University, 1-3 Miyakodani, Tatara, Kyotanabe-City 610-0394, Kyoto, Japan.
Yuki MatsuokaDepartment of Biomedical Engineering, Faculty of Life and Medical Sciences, Doshisha University, 1-3 Miyakodani, Tatara, Kyotanabe-City 610-0394, Kyoto, Japan.
Yuna MiyawakiDepartment of Biomedical Engineering, Faculty of Life and Medical Sciences, Doshisha University, 1-3 Miyakodani, Tatara, Kyotanabe-City 610-0394, Kyoto, Japan.
Shinichi KadowakiDepartment of Biomedical Engineering, Faculty of Life and Medical Sciences, Doshisha University, 1-3 Miyakodani, Tatara, Kyotanabe-City 610-0394, Kyoto, Japan.
Makiko NakaharaActualEyes Inc., D-egg, 1 Jizodani, Koudo, Kyotanabe-City 610-0332, Kyoto, Japan.
Yasushi MatsuokaActualEyes Inc., D-egg, 1 Jizodani, Koudo, Kyotanabe-City 610-0332, Kyoto, Japan.
Noriko KoizumiDepartment of Biomedical Engineering, Faculty of Life and Medical Sciences, Doshisha University, 1-3 Miyakodani, Tatara, Kyotanabe-City 610-0394, Kyoto, Japan.
Doshisha University · JP

Funding

ActualEyes Inc. The joint research and development expenses
6 · The paper itself

Abstract

Corneal endothelial decompensation is treated by the corneal transplantation of donor corneas, but donor shortages and other problems associated with corneal transplantation have prompted investigations into tissue engineering therapies. For clinical use, cells used in tissue engineering must undergo strict quality control to ensure their safety and efficacy. In addition, efficient cell manufacturing processes are needed to make cell therapy a sustainable standard procedure with an acceptable economic burden. In this study, we obtained 3098 phase contrast images of cultured human corneal endothelial cells (HCECs). We labeled the images using semi-supervised learning and then trained a model that predicted the cell centers with a precision of 95.1%, a recall of 92.3%, and an F-value of 93.4%. The cell density calculated by the model showed a very strong correlation with the ground truth (Pearson's correlation coefficient = 0.97,

Indexed as

artificial intelligencecellular therapycorneal endothelial celldeep learningtissue engineeringU-Net

Identifiers

PMID38247948
PMCPMC10813389
OpenAlexW4390752144

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.