Titlebook: Intelligent Data Analysis in Medicine and Pharmacology; Nada Lavra?,Elpida T. Keravnou,Bla? Zupan Book 1997 Springer Science+Business Medi

vascular

Prognosing the Survival Time of Patients with Anaplastic Thyroid Carcinoma using Machine Learningaim of this study was to determine which of the factors, known at the time of admission to the hospital, might predict survival of the patients with anaplastic thyroid carcinoma. Our aim was also to assess the relative importance of the factors and to identify potentially useful decision and regress

使害怕

Anticoagulants

Dementia Screening with Machine Learning Methodst accurate patient parameters that would discriminate 244 very mildly demented from 198 normally aging subjects. Attributes included age, sex and education plus responses to the Functional Activities Questionnaire, the Mini-Mental Status and Blessed Orientation, Memory and Concentration tests. The m

generic

顯而易見

出沒

Diterpene Structure Elucidation from 13C NMR-Spectra with Machine Learningbecause of their use as lead compounds in the search for new pharmaceutical effectors. The interpretation of diterpene .C NMR-spectra normally requires specialists with detailed spectroscopic knowledge and substantial experience in natural products chemistry, more specifically knowledge on peak patt

教育學(xué)

Using Inductive Logic Programming to Learn Rules that Identify Glaucomatous Eyese domain is glaucoma diagnosis where ocular fundus images are used to identify glaucomatous eyes. An ILP system called GKS was developed, not only to deal with low-level measurement data such as images but also produce diagnostic rules that are readable and comprehensive for interactions with medica

Hyperopia

Carcinogenesis Predictions Using Inductive Logic Programmingn our earlier research that demonstrated the use of Inductive Logic Programming (ILP) for predictions for the related problem of mutagenic activity amongst nitroaromatic molecules. Here we are concerned with predicting carcinogenic activity in rodent bioassays using data from the U.S. National Toxic

帶來

Cardioversion

Classification of Human Brain Waves Using Self-Organizing Mapsdes (channels), sampled at 128 Hz. Data vectors are extracted at intervals of half a second with a duration of one second each, resulting in vectors overlapping half a second. Before the training of the map, the sample vectors were compressed by either the Fast-Fourier-Transform or the Wavelet-Trans