ArticleUltrasound in medicine & biology2021
Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver.
Article in Ultrasound in medicine & biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 22 citations in OpenAlex.
- Migration of Deep Learning Models Across Ultrasound Scanners.IEEE transactions on bio-medical engineering · 2025Article
- Review
- Feasibility of Backscattering Coefficient Evaluation of Soft Tissue Using High-Frequency Annular Array Probe.Sensors (Basel, Switzerland) · 2024Article
- Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study.Sensors (Basel, Switzerland) · 2024Article
- Machine-to-Machine Transfer Function in Deep Learning-Based Quantitative Ultrasound.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024Article
- Deep Learning-Based Evaluation of Ultrasound Images for Benign Skin Tumors.Sensors (Basel, Switzerland) · 2023Article
- Applications of Deep Learning Algorithms to Ultrasound Imaging Analysis in Preclinical Studies on In Vivo Animals.Life (Basel, Switzerland) · 2023Review
- Calibrating Data Mismatches in Deep Learning-Based Quantitative Ultrasound Using Setting Transfer Functions.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2023Article
- A Data-Efficient Deep Learning Strategy for Tissue Characterization via Quantitative Ultrasound: Zone Training.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2023Article
- Abdominal virtual non-contrast images derived from energy spectrum CT to evaluate chemotherapy-related fatty liver disease.Quantitative imaging in medicine and surgery · 2023Article
- Quantitative Ultrasound: Experimental Implementation.Advances in experimental medicine and biology · 2023Article
- Quantitative Ultrasound: An Emerging Technology for Detecting, Diagnosing, Imaging, Evaluating, and Monitoring Disease.Advances in experimental medicine and biology · 2023Article
- Evaluation of Hepatic Fibrosis Using Ultrasound Backscattered Radiofrequency Signals and One-Dimensional Convolutional Neural Networks.Diagnostics (Basel, Switzerland) · 2022Article
- Artificial intelligence in liver ultrasound.World journal of gastroenterology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl
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.