ArticleNature methods2019
Author Correction: U-Net: deep learning for cell counting, detection, and morphometry.
Article in Nature methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed.
- Tumour infiltrating lymphocytes and survival after adjuvant chemotherapy in patients with gastric cancer: post-hoc analysis of the CLASSIC trial.British journal of cancer · 2023Trial
- C1M2: a universal algorithm for 3D instance segmentation, annotation, and quantification of irregular cells.Science China. Life sciences · 2023Article
- Predicting Recurrence in Pancreatic Ductal Adenocarcinoma after Radical Surgery Using an AX-Unet Pancreas Segmentation Model and Dynamic Nomogram.Bioengineering (Basel, Switzerland) · 2023Article
- A deep learning framework for quantitative analysis of actin microridges.NPJ systems biology and applications · 2023Article
- Deep learning-based molecular morphometrics for kidney biopsies.JCI insight · 2021Article
- The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis.Protein science : a publication of the Protein Society · 2021Article
- Code-Free Development and Deployment of Deep Segmentation Models for Digital Pathology.Frontiers in medicine · 2021Article
- Computational Methods for Single-Cell Imaging and Omics Data Integration.Frontiers in molecular biosciences · 2021Review
Corrections and comments
- Erratum for
Authors and funding
22 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the version of this paper originally published, one of the affiliations for Dominic Mai was incorrect: "Center for Biological Systems Analysis (ZBSA), Albert-Ludwigs-University, Freiburg, Germany" should have been "Life Imaging Center, Center for Biological Systems Analysis, Albert-Ludwigs-University, Freiburg, Germany." This change required some renumbering of subsequent author affiliations. These corrections have been made in the PDF and HTML versions of the article, as well as in any cover sheets for associated Supplementary Information.
Identifiers
30804552What OpenQuestion holds
Registered trials
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.