Extending the feature dictionary to support sophisticated feature interaction and classification
نویسندگان
چکیده
MEDAS, a Bayesian diagnostic system, includes a Feature Dictionary that contains descriptions of signs, symptoms, and test results, along with alternate medical terminology used in various fields and parts of the country. The Feature Dictionary has now been expanded to include feature interactions to support test selection and treatment protocols. The feature interactions required to provide this flexibility are drug side-effects and allergic reactions, contraindications IO tests and treatment, and drug interactions. Although the primary use of the dictionary is to store the feature information to be used by the MEDAS diagnostic system, adding further functionality allows other applications, both inside and outside of MEDAS to be supported. Generic and brand names of drugs appear as synonyms in the dictionary. This widens our abilities to translate data from one system lo another.
منابع مشابه
استفاده از نمایش پراکنده و همکاری دوربینها برای کاربردهای نظارت بینایی
With the growth of demand for security and safety, video-based surveillance systems have been employed in a large number of rural and urban areas. The problem of such systems lies in the detection of patterns of behaviors in a dataset that do not conform to normal behaviors. Recently, for behavior classification and abnormal behavior detection, the sparse representation approach is used. In thi...
متن کاملFeature Selection Using Multi Objective Genetic Algorithm with Support Vector Machine
Different approaches have been proposed for feature selection to obtain suitable features subset among all features. These methods search feature space for feature subsets which satisfies some criteria or optimizes several objective functions. The objective functions are divided into two main groups: filter and wrapper methods. In filter methods, features subsets are selected due to some measu...
متن کاملدو روش تبدیل ویژگی مبتنی بر الگوریتم های ژنتیک برای کاهش خطای دسته بندی ماشین بردار پشتیبان
Discriminative methods are used for increasing pattern recognition and classification accuracy. These methods can be used as discriminant transformations applied to features or they can be used as discriminative learning algorithms for the classifiers. Usually, discriminative transformations criteria are different from the criteria of discriminant classifiers training or their error. In this ...
متن کاملAutomatic Face Recognition via Local Directional Patterns
Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...
متن کاملModeling and design of a diagnostic and screening algorithm based on hybrid feature selection-enabled linear support vector machine classification
Background: In the current study, a hybrid feature selection approach involving filter and wrapper methods is applied to some bioscience databases with various records, attributes and classes; hence, this strategy enjoys the advantages of both methods such as fast execution, generality, and accuracy. The purpose is diagnosing of the disease status and estimating of the patient survival. Method...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1989