ReviewUltrasound in medicine & biology2022
State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses.
Review in Ultrasound in medicine & biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 18 papers.
What it found
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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.
Synergistic Assessment of Ultrasound Data and Respiratory physiOlogical Signals in luNg Diseases
Assessment of Pulmonary EmphySema: the Clinical -ULtrasonographic APproach to chronIc Obstructive Pulmonary Disease
Who cites it
18 citing papers in PubMed.
- Quantitative lung ultrasound spectroscopy: First comparison with gold standard computed tomography scan and standard lung ultrasound for diagnosis of pneumonia versus cardiogenic pulmonary edema.The ultrasound journal · 2026Article
- On the interception of the optimal imaging plane for pleural line scanning with automatic robot assisted lung ultrasound: An experimental study.The ultrasound journal · 2026Article
- Lung Ultrasound Imaging Dataset for Accurate Detection and Localization of LUS Vertical Artifact.Scientific data · 2025Article
- Evaluating deep learning approaches for AI-assisted lung ultrasound diagnosis: an international multi-center and multi-scanner study.The ultrasound journal · 2025Article
- AI Enhances Lung Ultrasound Interpretation Across Clinicians with Varying Expertise Levels.Diagnostics (Basel, Switzerland) · 2025Article
- Lung re-aeration assessment by ultrasound during mechanical ventilation: Current knowledge of literature review.Multidisciplinary respiratory medicine · 2025Article
- Impact of ultrasound settings on lung vertical artefacts: an observational study in mechanically ventilated patients.ERJ open research · 2025Article
- Article
- A machine learning-based lung ultrasound algorithm for the diagnosis of acute heart failure.Internal and emergency medicine · 2024Article
- To B or not to B-lines.Journal of anesthesia, analgesia and critical care · 2024Article
- Article
- Improving the Generalizability and Performance of an Ultrasound Deep Learning Model Using Limited Multicenter Data for Lung Sliding Artifact Identification.Diagnostics (Basel, Switzerland) · 2024Article
- An Interpretable Neonatal Lung Ultrasound Feature Extraction and Lung Sliding Detection System Using Object Detectors.IEEE journal of translational engineering in health and medicine · 2024Article
- Can Artificial Intelligence Aid Diagnosis by Teleguided Point-of-Care Ultrasound? A Pilot Study for Evaluating a Novel Computer Algorithm for COVID-19 Diagnosis Using Lung Ultrasound.AI (Basel, Switzerland) · 2023Article
- Advancing healthcare through thoracic ultrasound research in older patients.Aging clinical and experimental research · 2023Review
- Ultrasound imaging of lung disease and its relationship to histopathology: An experimentally validated simulation approach.The Journal of the Acoustical Society of America · 2023Article
- COVID-19 Lung Ultrasound Scores and Lessons from the Pandemic: A Narrative Review.Diagnostics (Basel, Switzerland) · 2023Review
- The Role of Ultrasound in the Diagnosis of Pulmonary Infection Caused by Intracellular, Fungal Pathogens and Mycobacteria: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung ultrasound (LUS) has been increasingly expanding since the 1990s, when the clinical relevance of vertical artifacts was first reported. However, the massive spread of LUS is only recent and is associated with the coronavirus disease 2019 (COVID-19) pandemic, during which semi-quantitative computer-aided techniques were proposed to automatically classify LUS data. In this review, we discuss the state of the art in LUS, from semi-quantitative image analysis approaches to quantitative techniques involving the analysis of radiofrequency data. We also discuss recent in vitro and in silico studies, as well as research on LUS safety. Finally, conclusions are drawn highlighting the potential future of LUS.
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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.