Search results for "Neural Networks"
showing 10 items of 599 documents
A NEURAL NETWORK PRIMER
1994
Neural networks are composed of basic units somewhat analogous to neurons. These units are linked to each other by connections whose strength is modifiable as a result of a learning process or algorithm. Each of these units integrates independently (in paral lel) the information provided by its synapses in order to evaluate its state of activation. The unit response is then a linear or nonlinear function of its activation. Linear algebra concepts are used, in general, to analyze linear units, with eigenvectors and eigenvalues being the core concepts involved. This analysis makes clear the strong similarity between linear neural networks and the general linear model developed by statisticia…
De novo liquid biopsy and radio genomic diagnostic approach with combined deep learning artificial neural networks for NSCLC
2022
Each year, the mortality rate and incidence of non-small cell lung cancer (NSCLC) are dramatically increasing. The introduction of liquid biopsy in the clinical practice of NSCLC has completely revolutionized the approach to such neoplasm since is generally detected through complex and invasive procedures and unfortunately at advanced stages. The importance and innovation of liquid biopsy are linked with the possibility of cancer detection at every stage, adjuvant treatment, resistance genotyping, systematic initiation of treatment, minimal residual disease, early detection of relapse, and screening of NSCLC. Circulating tumor DNA (ctDNA) is now emerging as a non-invasive biomarker that wil…
Absorption edge in silica glass
2005
Measurements of optical absorption in the v-UV range in a variety of silica glass are used to determine the width of the absorption edge (Urbach energy). Measured values range from 60 meV up to 180 meV. So high a variability over silica types is tentatively ascribed to the different disorder degree, which characterizes different materials.
Molecular mode-coupling theory applied to a liquid of diatomic molecules
2000
We study the molecular mode coupling theory for a liquid of diatomic molecules. The equations for the critical tensorial nonergodicity parameters ${\bf F}_{ll'}^m(q)$ and the critical amplitudes of the $\beta$ - relaxation ${\bf H}_{ll'}^m(q)$ are solved up to a cut off $l_{co}$ = 2 without any further approximations. Here $l,m$ are indices of spherical harmonics. Contrary to previous studies, where additional approximations were applied, we find in agreement with simulations, that all molecular degrees of freedom vitrify at a single temperature $T_c$. The theoretical results for the non ergodicity parameters and the critical amplitudes are compared with those from simulations. The qualitat…
An integrated framework for risk profiling of breast cancer patients following surgery.
2006
Objective: An integrated decision support framework is proposed for clinical oncologists making prognostic assessments of patients with operable breast cancer. The framework may be delivered over a web interface. It comprises a triangulation of prognostic modelling, visualisation of historical patient data and an explanatory facility to interpret risk group assignments using empirically derived Boolean rules expressed directly in clinical terms. Methods and materials: The prognostic inferences in the interface are validated in a multicentre longitudinal cohort study by modelling retrospective data from 917 patients recruited at Christie Hospital, Wilmslow between 1983 and 1989 and predictin…
The relaxation dynamics of a simple glass former confined in a pore
2000
We use molecular dynamics computer simulations to investigate the relaxation dynamics of a binary Lennard-Jones liquid confined in a narrow pore. We find that the average dynamics is strongly influenced by the confinement in that time correlation functions are much more stretched than in the bulk. By investigating the dynamics of the particles as a function of their distance from the wall, we can show that this stretching is due to a strong dependence of the relaxation time on this distance, i.e. that the dynamics is spatially very heterogeneous. In particular we find that the typical relaxation time of the particles close to the wall is orders of magnitude larger than the one of particles …
A Neural Network model for the Evaluation of Text Complexity in Italian Language: a Representation Point of View
2018
Abstract The goal of a text simplification system (TS) is to create a new text suited to the characteristics of a reader, with the final goal of making it more understandable.The building of an Automatic Text Simplification System (ATS) cannot be separated from a correct evaluation of the text complexity. In fact the ATS must be capable of understanding if a text should be simplified for the target reader or not. In a previous work we have presented a model capable of classifying Italian sentences based on their complexity level. Our model is a Long Short Term Memory (LSTM) Neural Network capable of learning the features of easy-to-read and complex-to-read sentences autonomously from a anno…
Gravitational-wave parameter inference using Deep Learning
2021
We explore machine learning methods to detect gravitational waves (GW) from binary black hole (BBH) mergers using deep learning (DL) algorithms. The DL networks are trained with gravitational waveforms obtained from BBH mergers with component masses randomly sampled in the range from 5 to 100 solar masses and luminosity distances from 100 Mpc to, at least, 2000 Mpc. The GW signal waveforms are injected in public data from the O2 run of the Advanced LIGO and Advanced Virgo detectors, in time windows that do not coincide with those of known detected signals, and the data from each detector in the Advanced LIGO and Advanced Virgo network is combined into a unique RGB image. We show that a clas…
2020
Abstract A person-centered approach was used to identify the profiles of symptoms of psychological ill-being among Finnish upper secondary education students (N = 2889); to examine whether gender and educational track (i.e., academic or vocational) are associated with these profiles; and to investigate the role of profiles in school dropout intentions. Using latent profile analysis, one asymptomatic profile (normative, 79.2%) and three symptomatic profiles (internalizing symptoms, 9.1%; externalizing symptoms, 9.1%; and comorbid symptoms, 2.6%) were identified. Boys in the vocational track were overrepresented in the externalizing-symptoms profile, whereas girls in both tracks were overrepr…
Dynamic anomalies at the glass transition of organic van der Waals liquids
1993
Abstract The paper discusses the question of whether there is a characteristic temperature T c above the calorimetric glass transition temperature T g . Mode-coupling theory (MCT) predicts a crossover from liquid- to solid-like dynamics at T c . Neutron scattering and gradient NMR experiments have been carried out to test MCT using the molecular van der Waals liquid ortho -terphenyl as a model system. A significant anomaly of the Debye—Waller factor and a “decoupling” of self-diffusion from viscosity support the MCT predictions. A critical discussion of the relevance of such tests and of the limitations of neutron scattering is presented.