Search results for "Artificial Intelligence"
showing 10 items of 6122 documents
Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules.
2016
We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined.…
Recognition of Root Canal Orifices in Video Sequences as a Future Support System During Endodontic Treatment
2009
Abstract Introduction The objective of this study was to show the practical application of computer-aided techniques for detecting root canal orifices through the access cavity using a video camera mounted on a microscope. Methods A minimum distance classification image recognition algorithm was tested in an in vitro study to assess the possibilities of computer-aided recognition of root canal orifices. A Motic DM143 digital stereo microscope (Motic Germany GmbH, Wetzlar, Germany) was used because it includes a video camera that can be connected via USB1.1 to any computer. Results The newly developed software is capable of communicating with a video camera and can automatically detect the r…
Subgrouping factors influencing migraine intensity in women: A semi-automatic methodology based on machine learning and information geometry
2019
[EN] Background Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques. Objective The aim of this study was to analyze critical features that permit the differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks by using machine learning algorithms. Methods Sixty-seven women with migraine participated. Clinical features of migraine, related disability (Migraine Disability Assessment Scale), anxiety/depressive levels (Hospital Anxiety and Depression Scale), anxiety state/trait levels (S…
Surrogate data approaches to assess the significance of directed coherence: Application to EEG activity propagation
2009
This paper addresses the topic of evaluating the significance of frequency domain measures of causal coupling in multivariate time series through generation of surrogate data. The considered approaches are the traditional Fourier Transform (FT) algorithm and a new causal FT (CFT) algorithm for surrogate data generation. Both algorithms preserve the FT modulus of the original series; differences are in the phase relationships, that are completely destroyed for FT surrogates and imposed after switching off the link over the considered causal direction for CFT surrogates. The ability of the algorithms to assess causality in the frequency domain was tested using the directed coherence as discri…
On the complementarity of holistic and analytic approaches to performance assessment scoring.
2019
BACKGROUND A holistic approach to performance assessment recognizes the theoretical complexity of multifaceted critical thinking (CT), a key objective of higher education. However, issues related to reliability, interpretation, and use arise with this approach. AIMS AND METHOD Therefore, we take an analytic approach to scoring students' written responses on a performance assessment. We focus on the complementarity of holistic and analytic approaches and on whether theoretically developed analytical scoring rubrics can produce sub-scores that may measure the 'whole' performance in a holistic assessment. SAMPLE We use data from the Wind Turbines performance assessment, developed in the iPAL p…
Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes
2015
[EN] Patients suffering from atrial fibrillation can be classified into different subtypes, according to the temporal pattern of the arrhythmia and its recurrence. Nowadays, clinicians cannot differentiate a priori between the different subtypes, and patient classification is done afterwards, when its clinical course is available. In this paper we present a comparison of classification performances when differentiating paroxysmal and persistent atrial fibrillation episodes by means of support vector machines. We analyze short surface electrocardiogram recordings by extracting modulus and phase features from several time-frequency transforms: short-time Fourier transform, Wigner-Ville, Choi-…
Temporal Structure of Human Gaze Dynamics Is Invariant During Free Viewing.
2015
We investigate the dynamic structure of human gaze and present an experimental study of the frequency components of the change in gaze position over time during free viewing of computer-generated fractal images. We show that changes in gaze position are scale-invariant in time with statistical properties that are characteristic of a random walk process. We quantify and track changes in the temporal structure using a well-defined scaling parameter called the Hurst exponent, H. We find H is robust regardless of the spatial complexity generated by the fractal images. In addition, we find the Hurst exponent is invariant across all participants, including those with distinct changes to higher or…
Normative data on the familiarity and difficulty of 196 Spanish word fragments
2005
In this article, normative data on the familiarity and difficulty of 196 single-solution Spanish word fragments are presented. The database includes the following indices: difficulty, familiarity, frequency, number of meanings, number of letters given in the fragment, first and/or last letters given, and ratio of letters to blanks. A factor analysis was performed on difficulty, and two factors were obtained. Frequency, familiarity, and number of meanings loaded highly on the first factor, which we consider to measure lexical processes, whereas number of letters in the fragment, first and/or last letters given, and ratio of letters to blanks loaded highly on the second factor, which we judge…
Simulating Images Seen by Patients with Inhomogeneous Sensitivity Losses
2012
PURPOSE We aim to simulate how colored images are perceived by subjects with local achromatic and chromatic contrast sensitivity losses in the visual field (VF). METHODS The spatiochromatic corresponding pair algorithm, introduced in a previous article (J Opt Soc Am (A) 2004;21:176-186), has been implemented with a linear model of the visual system. Spatial information is processed separately by the chromatic and achromatic mechanisms by means of a multiscale model, with sensors selective to frequency, orientation, and spatial position, whose mechanism-dependent relative weights change with the spatial location of the image. These weights have been obtained from perimetric data from a patie…
The accuracy and reproducibility of the endometrial receptivity array is superior to histology as a diagnostic method for endometrial receptivity
2013
Objective To compare the accuracy and reproducibility of the endometrial receptivity array (ERA) versus standard histologic methods. Design A comparative prospective study (May 2008–May 2012). Setting University-affiliated infertility clinic. Patient(s) Eighty-six healthy oocyte donors, regularly cycling, aged 20–34 years with a body mass index (BMI) of 19–25 kg/m 2 . Intervention(s) Endometrial biopsies were collected throughout the menstrual cycle. For the accuracy study, 79 samples were grouped into two cohorts: the training set (n = 79) for ERA machine-learning training and dating, and a dating subset (n = 49) for comparison between histologic and ERA dating. For the reproducibility stu…