ArticleBiomedical optics express2020
Qualitative and quantitative detection of liver injury with terahertz time-domain spectroscopy.
Article in Biomedical optics express, 2020. 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
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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.
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Who cites it
8 citing papers in PubMed, 28 citations in OpenAlex.
- Study on the detection method of biological characteristics of hepatoma cells based on terahertz time-domain spectroscopy.Biomedical optics express · 2023Article
- Measurement of tissue optical properties in a wide spectral range: a review [Invited].Biomedical optics express · 2023Review
- Moxa Wool in Different Purities and Different Growing Years Measured by Terahertz Spectroscopy.Plant phenomics (Washington, D.C.) · 2022Article
- Moisture adsorption by decellularized bovine pericardium collagen matrices studied by terahertz pulsed spectroscopy and solid immersion microscopy.Biomedical optics express · 2021Article
- Cellular effects of terahertz waves.Journal of biomedical optics · 2021Review
- Machine Learning Techniques for THz Imaging and Time-Domain Spectroscopy.Sensors (Basel, Switzerland) · 2021Review
- In situ terahertz monitoring of an ice ball formation during tissue cryosurgery: a feasibility test.Journal of biomedical optics · 2021Article
- Quantitative analysis of homocysteine in liquid by terahertz spectroscopy.Biomedical optics express · 2020Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Terahertz technology has been widely used as a nondestructive and effective detection method. Herein, terahertz time-domain spectroscopy was used to detect drug-induced liver injury in mice. Firstly, the boxplots were used to detect abnormal data. Then the maximal information coefficient method was used to search for the features strongly correlated with the degree of injury. After that, the liver injury model was built using the random forests method in machine learning. The results show that this method can effectively identify the degree of liver injury and thus provide an auxiliary diagnostic method for detecting minor liver injury.
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.