ArticleSensors (Basel, Switzerland)2019
Discrimination of Different Species of Dendrobium with an Electronic Nose Using Aggregated Conformal Predictor.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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Who cites it
4 citing papers in PubMed.
- Artificial intelligence and synthetic biology in traditional Chinese medicine: revolutionizing public health applications.Frontiers in plant science · 2026Review
- Identification of Dendrobium Using Laser-Induced Breakdown Spectroscopy in Combination with a Multivariate Algorithm Model.Foods (Basel, Switzerland) · 2024Article
- Studying and mitigating the effects of data drifts on ML model performance at the example of chemical toxicity data.Scientific reports · 2022Article
- Research on Distinguishing Fish Meal Quality Using Different Characteristic Parameters Based on Electronic Nose Technology.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
A method using electronic nose to discriminate 10 different species of dendrobium, which is a kind of precious herb with medicinal application, was developed with high efficiency and low cost. A framework named aggregated conformal prediction was applied to make predictions with accuracy and reliability for E-nose detection. This method achieved a classification accuracy close to 80% with an average improvement of 6.2% when compared with the results obtained by using traditional inductive conformal prediction. It also provided reliability assessment to show more comprehensive information for each prediction. Meanwhile, two main indicators of conformal predictor, validity and efficiency, were also compared and discussed in this work. The result shows that the approach integrating electronic nose with aggregated conformal prediction to classify the species of dendrobium with reliability and validity is promising.
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Registered trials
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