The purpose of today’s study is to build up a precise constitution diagnostic method based solely for the individual’s physical characteristics, regardless of psychologic traits, characteristics of clinical medicine, and genetic factors. improved analysis prediction and can serve to build up an individual and automated constitution analysis software for improvement of the effectiveness of prescribed medications and development of personalized medicine. 1. Introduction Due to the development of medicine and advances of biotechnology and information technology, the midpoint of medical treatment has shifted away from common treatments of a Zibotentan certain disease to personalized medicine [1C8]. Consistent with this paradigm, there has been an explosion of interest in alternative oriental medicines and in a fusion of oriental and western medicines [9C16]. One of the core research areas of personalized medicine in western and oriental medicine is to understand the psychological characteristics, morphological traits, genetic characteristics, and constitution of individuals. The human constitution has been researched in western and oriental medicine for a long time. For example, Hippocrates suggested that the human constitution could be attributed to four kinds of substances (blood, phlegm, choler, and black bile) [4]. Wang classified humans into seven constitutional groups using physiological and physical status [4, 17]. Similarly, Lee classified humans into four Sasang constitutional types as TE (Teaeumin), TY (Taeyangin), SE (Soeumin), and SY (Soyangin) based on physiological, psychological, and physical characteristics [2, 11C13, 15]. Personal constitution diagnosis is very important to several reasons. First of all, folks have vulnerability to particular illnesses according with their specific mental characteristics, genetic features, and morphological qualities. Therefore, risk elements for particular illnesses can be determined according to a person’s constitution in the first phases of disease development [18]. Secondly, medication response to recommended medication varies with personal constitution [11]. Therefore, the effectiveness of prescribed medication could be improved if we realize the patient’s constitution. Many reports on Sasang constitution have already been conducted. For the association of Sasang illnesses and constitutions as well as the difference of constitutional types, many researchers released constitution analysis strategies [1, 4, 5, 8, 12, 13, 15, 18C23]. Music et al. [22] categorized TE and SE among the constitutional types using pores and skin elasticity from the hands and demonstrated that elasticity from the TE type was greater than that of the SE type. Their Zibotentan constitution diagnosis measured hand skin elasticity predicated on a questionnaire survey of elasticity and thickness of your skin. The restrictions of the analysis were that tests were performed in mere TE and SE types rather than in Zibotentan the TY and SY types, and elasticity measurements had been performed only IGF1R for the family member back from the hands. Choi et al. [18] researched the distribution of insulin resistance using multivariate logistic regression analysis and features such as age, cholesterol level, smoker/nonsmoker, diastolic blood pressure, and insulin in subjects of each constitutional type. They demonstrated that prevalence of insulin resistance differs according to Sasang constitution type and suggested that personal constitution type can act as an independent risk factor for insulin resistance. An association study between genome-wide SNP (simple nucleotide polymorphisms) profiles and Sasang constitution types for a more accurate Sasang constitution diagnosis was conducted via experiments using 353,202 SNPs from 60 DNAs by Yin et al [8]. They observed that 5,692 SNPs in TE versus SE association analysis were significantly different, 7,542 SNPs in SE versus SY were significantly different, and 4,083 SNPs in SY versus TE were significantly different. The detailed contents of Sasang constitutional medicine are described in references [2, 12], and the research on face or speech signals are described in references [24C28]. Until recently, previous studies that used face, SNPs, skin, body shape, and speech signals have focused primarily on difference analysis among constitutional types; the study of diagnosis prediction is rare. In this study, we focus on Sasang constitution diagnosis using morphological characteristics that are easily accessible to researchers and doctors. The motivations of this study are as follows: first, how do we obtain useful and necessary features that present interactions between morphological features and corresponding constitutional types? Second, so how exactly does a single make use of these features to develop a precise and effective medical diagnosis model? We make the next contributions towards the field of constitution medical diagnosis. Propose a easily available and book method for a precise and complete constitution medical diagnosis using the mix of cosmetic characteristics and talk signals in age group- and gender-specific groupings. Our technique may support the path of improved medical diagnosis prediction and can serve to build up an individual and automated constitution medical diagnosis device for improvement of the potency of prescribed medicines and advancement of individualized medication. Suggest discriminative and significant features for constitution medical diagnosis via statistical evaluation, and identify a concise and useful feature subset relative to gender and age. Evaluation of outcomes shall serve.