Search results for " PCA"

Choline PET/CT Features to Predict Survival Outcome in High Risk Prostate Cancer Restaging: A Preliminary Machine-Learning Radiomics Study

2020

Background Radiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging but to date its role has not been investigated for Cho-PET in prostate cancer. The potential application of radiomics features analysis using a machine-learning radiomics algorithm was evaluated to select 18F-Cho PET/CT imaging features to predict disease progression in PCa. Methods We retrospectively analyzed high-risk PCa patients who underwent restaging 18F-Cho PET/CT from November 2013 to May 2018. 18F-Cho PET/CT studies and related structures containing volumetric segmentations were imported in the "CGITA" toolbox to extract imaging features from each lesion. A Machine-learning model h…

A Multivariate Analysis on Non-nucleoside HIV-1 Reverse Transcriptase Inhibitors and Resistance Induced by Mutation

2003

This paper describes the use of multivariate statistical procedure PCA as a tool to explore the inhibitory activity of classes of NNRTIs against HIV-1 viruses (wild type and more frequent mutants, Y181C, V106A, K103N, L100I) and against RT enzyme. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the fifty five derivatives considered in this study. The best results were obtained in the case of L100I and K103N mutants for which the higher number of assignments was found when the principal components derived from the descriptors were used. On this basis this statistical approach is proposed as a reliab…

Caratterizzazione chimico-morfologica di accessioni spontanee di origano siciliano (Origanum heracleoticum L.) del territorio dei monti Nebrodi

2009

Il genere Origano è estremamente diffuso nel bacino del Mediterraneo, con diverse specie presenti nel territorio siciliano. Il comprensorio dei Monti Nebrodi (Sicilia N-E), esteso per circa 200.000 ettari, è una delle aree siciliane in cui è presente la massima biodiversità vegetale; l'area è caratterizzato prevalentemente dalla presenza di Origanum heracleoticum, reperibile in ambienti ecologicamente anche assai diversificati. Con l'obiettivo di acquisire informazioni utili ai fini della caratterizzazione delle accessioni di Origanum heracleoticum spontanee nel comprensorio nebroideo, a partire dal 2007 è stato avviato su di esse un lavoro di ricognizione e collezione sistematica. Campioni…

Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery

2021

Non-photosynthetic vegetation (NPV) biomass has been identified as a priority variable for upcoming spaceborne imaging spectroscopy missions, calling for a quantitative estimation of lignocellulosic plant material as opposed to the sole indication of surface coverage. Therefore, we propose a hybrid model for the retrieval of non-photosynthetic cropland biomass. The workflow included coupling the leaf optical model PROSPECT-PRO with the canopy reflectance model 4SAIL, which allowed us to simulate NPV biomass from carbon-based constituents (CBC) and leaf area index (LAI). PROSAIL-PRO provided a training database for a Gaussian process regression (GPR) algorithm, simulating a wide range of non…

Data-driven analysis for fMRI during naturalistic music listening

2017

Interest towards higher ecological validity in functional magnetic resonance imaging (fMRI) experiments has been steadily growing since the turn of millennium. The trend is reflected in increasing amount of naturalistic experiments, where participants are exposed to the real-world complex stimulus and/or cognitive tasks such as watching movie, playing video games, or listening to music. Multifaceted stimuli forming parallel streams of input information, combined with reduced control over experimental variables introduces number of methodological challenges associated with isolating brain responses to individual events. This exploratory work demonstrated some of those methodological challeng…

The assessment of EU photovoltaic trend by using PCA and DEA techniques

2012

Aim of this work is, firstly, to produce a synthetic indicator able to identify the main factors that allowed the Photovoltaic (“PV” since now) diffusion from 1996 (PV wide diffusion starting date) to 2010, in 14 selected countries (on the basis of the best performance at EU level, showed by the time series considered) and, secondly, we want to evaluate the technical efficiency of these countries in terms of efficient resources utilization and cost efficiency. For this scope a two steps analysis is performed. In the first step, by using the Principal Component Analysis (PCA) technique, we will identify specific weights of the variables considered for each year, and the roles (in terms of we…

Study of quantitative and qualitative variations in essential oils of Sicilian Rosmarinus officials L.

2015

In this study the chemical characterizations of 10 sicilian biotypes of Rosmarinus officinalis L. essential oils are reported. The main goal was to analyze the relationship between the essential oils yield and the geographical distribution of the species plants. The essential oils were analyzed by GC-FID and GC-MS. The statistical methods Hierarchical Cluster Analysis and Principal Component Analysis were used to cluster biotypes according to the chemical composition of the essential oils. The essential oil yield ranged from 0.8 - 2.3 (v/w). 82 compounds have been identified, these represent 96.7-99.9% of the essential oil. The compounds mostly represented in the essential oils were: 1.8- C…

PCA and QSAR/QSPR used in combination to predict the drugs mechanism of action. An application to the NCI ACAM Database

2008

Feature selection on a dataset of protein families: from exploratory data analysis to statistical variable importance

2016

Proteins are characterized by several typologies of features (structural, geometrical, energy). Most of these features are expected to be similar within a protein family. We are interested to detect which features can identify proteins that belong to a family, as well as to define the boundaries among families. Some features are redundant: they could generate noise in identifying which variables are essential as a fingerprint and, consequently, if they are related or not to a function of a protein family. We defined an original approach to analyze protein features for defining their relationships and peculiarities within protein families. A multistep approach has been mainly performed in R …

Generation of stimulus features for analysis of FMRI during natural auditory experiences

2014

In contrast to block and event-related designs for fMRI experiments, it becomes much more difficult to extract events of interest in the complex continuous stimulus for finding corresponding blood-oxygen-level dependent (BOLD) responses. Recently, in a free music listening fMRI experiment, acoustic features of the naturalistic music stimulus were first extracted, and then principal component analysis (PCA) was applied to select the features of interest acting as the stimulus sequences. For feature generation, kernel PCA has shown its superiority over PCA in various applications, since it can implicitly exploit nonlinear relationship among features and such relationship seems to exist genera…