ArticleAmerican journal of respiratory and critical care medicine2018
Artificial Intelligence and Chest Imaging. Will Deep Learning Make Us Smarter?
Article in American journal of respiratory and critical care medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Article
- A 3D-CNN model with CT-based parametric response mapping for classifying COPD subjects.Scientific reports · 2021Article
- Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19.Machine vision and applications · 2020Article
- Update in Chronic Obstructive Pulmonary Disease 2018.American journal of respiratory and critical care medicine · 2019Article
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What 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.