Search results for "Decision tree model"
showing 6 items of 6 documents
A Simple Method to Predict Blood-Brain Barrier Permeability of Drug- Like Compounds Using Classification Trees
2017
Background: To know the ability of a compound to penetrate the blood-brain barrier (BBB) is a challenging task; despite the numerous efforts realized to predict/measure BBB passage, they still have several drawbacks. Methods: The prediction of the permeability through the BBB is carried out using classification trees. A large data set of 497 compounds (recently published) is selected to develop the tree model. Results: The best model shows an accuracy higher than 87.6% for training set; the model was also validated using 10-fold cross-validation procedure and through a test set achieving accuracy values of 86.1% and 87.9%, correspondingly. We give a brief explanation, in structural terms, o…
Negative biopsy of focal hepatic lesions: Decision tree model for patient management
2019
OBJECTIVE. The purpose of this study was to investigate patient- and procedure-related variables affecting the false-negative rate of ultrasound (US)-guided liver biopsy and to develop a standardized patient-tailored predictive model for the management of negative biopsy results. MATERIALS AND METHODS. We retrospectively included 389 patients (mean age ± SD, 62 ± 12 years old) who had undergone US-guided liver biopsy of 405 liver lesions between January 1, 2013, and June 30, 2015. We collected multiple patient- and procedure-related variables. By comparing pathology reports of biopsy and the reference standard (further histology or imaging follow-up), we were able to categorize the biopsy r…
Communication complexity in a 3-computer model
1996
It is proved that the probabilistic communication complexity of the identity function in a 3-computer model isO(√n).
Comparison of machine learning models for gully erosion susceptibility mapping
2020
© 2019 China University of Geosciences (Beijing) and Peking University Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory, especially in the Northern provinces. A number of studies have been recently undertaken to study this process and to predict it over space and ultimately, in a broader national effort, to limit its negative effects on local communities. We focused on the Bastam watershed where 9.3% of its surface is currently affected by gullying. Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability. However, unlike the bivariate statistical models, their structu…
Toward Approximate GML Retrieval Based on Structural and Semantic Characteristics
2010
International audience; GML is emerging as the new standard for representing geographic information in GISs on the Web, allowing the encoding of structurally and semantically rich geographic data in self describing XML-based geographic entities. In this study, we address the problem of approximate querying and ranked results for GML data and provide a method for GML query evaluation. Our method consists of two main contributions. First, we propose a tree model for representing GML queries and data collections. Then, we introduce a GML retrieval method based on the concept of tree edit distance as an efficient means for comparing semi-structured data. Our approach allows the evaluation of bo…
Reliability of a decision-tree model in predicting occupational lead poisoning in a group of highly exposed workers
2016
Objective This study aimed to provide the toxicological profile of some lead-exposed workers and obtain a predictive model for lead poisoning. Methods Data regarding external and absorbed exposure were collected from 585 subjects employed in ten metallurgical production departments. Airborne lead concentration, blood lead level (BLL), cumulative blood lead index (CBLI), urine delta-aminolevulinic acid (DALA), age, workplace/section, exposure period, and whether reported lead poisoning as occupational disease were examined using ANOVA, and, post-ANOVA, Pearson correlation matrix, PCA (principal component analysis), decision-tree modeling, and logistic modeling. Results BLL was less sensitive…