This paper is marked retracted in the scholarly record (OpenAlex). Interpret its findings with caution.
Retraction Note: A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications
Hadi Hashemzadeh, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Mario Rothbauer, Peter Ertl, Hossein Naderi-Manesh

Abstract
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsAI in cancer detection · Radiomics and Machine Learning in Medical Imaging · Brain Tumor Detection and Classification
Retraction of: Scientific Reports 10.1038/s41598-021-89352-8, published online 07 May 2021
The Editors have retracted this Article.
Following publication, the Editors were alerted to the use of non-standard phrasing which deviates from established scientific terminology. Investigation by the Editors have uncovered further issues, as outlined below:
- Some text appears to be reproduced verbatim or inappropriately paraphrased from previously-published work with no overlapping authors such as^1,2^.
- Some microscopy images in Figure 2 do not show DAPI staining and therefore appear to be inconsistent with the staining protocol as described in the methods. Further clarifications provided by the Authors in this regard were also discrepant.
- Number of images in the augmented datasets used for training the models are not reported in the Article. The Editors were also unable to conclusively confirm the numbers as the Authors did not provide the augmented dataset or laboratory records as requested.
The Editors therefore no longer have confidence in the findings presented in the Article.
Peter Ertl and Hossein Naderi-Manesh did not respond to correspondence regarding this retraction. The other Authors disagree with this retraction.
