Terahertz waves have unique properties and advantages, which makes it gain increasing attention and applications in the biomedical field. Burns is a common clinical trauma. Since the water sensitive and non destructive characteristics of terahertz, terahertz imaging techniques can be used to detect burns. So far, terahertz imaging technology in the assessment of burn injuries has been developed from ex vivo to in vivo, and high resolution images can be obtained through the gauzes and plasters. In this paper, we mainly introduces the application of terahertz imaging technology and development in the assessment of burn injuries.
Parkinson's disease (PD) diagnosis based on speech data has been proved to be an effective way in recent years. There are still some problems on preprocessing samples, ensemble learning, and so on. The problems can further cause misleading of classifiers, unsatisfactory classification accuracy and stability. This paper proposed a new diagnosis algorithm of PD by combining multi-edit sample selection method and random forest. At the end of it, this paper presents a group of experiments carried out with the newest public datasets. Experimental results showed that this proposed algorithm realized the classification of the samples and the subjects of PD. Furthermore, it achieved average classification accuracy of 100% and obtained improvement of up to 29.44% compared to those provided by the subjects. This paper proposes a new speech diagnosis algorithm for PD based on instance selection; and the method algorithm has a higher and more stable classification accuracy, compared with the other algorithms.