- Deep learning approach for classification of chondrocytes in rats
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Kang JS
- KMID: 2528092
- J Biomed Transl Res.
- 2022 Mar;23(1):1-6.
- doi: 10.12729/jbtr.2022.23.1.1
The rapid development of computer vision and deep learning has enabled these technologies to be applied to the automated classification and counting of microscope images, there-by relieving of some burden... -
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- Machine learning-based risk factor analysis for periodontal disease from a Korean National Survey
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Shon HS, Choi ES, Cho YS, Cha EJ, Kang TG, Kim KA
- KMID: 2528096
- J Biomed Transl Res.
- 2022 Mar;23(1):17-28.
- doi: 10.12729/jbtr.2022.23.1.17
Periodontal disease is a chronic but treatable condition which often does not cause pain during the initial stages of the illness. Lack of awareness of symptoms can delay initiation of... -
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- Anticoccidial effects of the Houttuynia cordata extract on experimental animal infection model
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Lee HS, Kim O
- KMID: 2528098
- J Biomed Transl Res.
- 2022 Mar;23(1):29-33.
- doi: 10.12729/jbtr.2022.23.1.29
Coccidiosis is caused by infection of Eimeria species and an significant parasitic disease in poultry. Various kinds of natural products have been studied to find alternative treatments for coccidiosis in... -
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- Quantitative analysis and risk assessment on total mercury and methyl mercury in seafood distributed in Daejeon
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Lee S, Oh S, Shin S, Kim D, Lee J, Kang H, Jo G
- KMID: 2528094
- J Biomed Transl Res.
- 2022 Mar;23(1):7-16.
- doi: 10.12729/jbtr.2022.23.1.7
Mercury and its compounds are globally managed chemicals as risks to the human body and ecosystem. It mainly enters the human body through ingestion of seafood, especially, methylmercury causes serious... -
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