Literature DB >> 32237773

Spectral forecast: A general purpose prediction model as an alternative to classical neural networks.

Paul A Gagniuc1, Constantin Ionescu-Tirgoviste2, Elvira Gagniuc3, Manuella Militaru3, Lawrence Chukwudi Nwabudike4, Bujorel Ionel Pavaloiu1, Andrei Vasilăţeanu1, Nicolae Goga1, George Drăgoi1, Irinel Popescu2, Simona Dima2.   

Abstract

Here, we describe a general-purpose prediction model. Our approach requires three matrices of equal size and uses two equations to determine the behavior against two possible outcomes. We use an example based on photon-pixel coupling data to show that in humans, this solution can indicate the predisposition to disease. An implementation of this model is made available in the supplementary material.

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Year:  2020        PMID: 32237773     DOI: 10.1063/1.5120818

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  3 in total

1.  Identifying geographically differentiated features of Ethopian Nile tilapia (Oreochromis niloticus) morphology with machine learning.

Authors:  Wilfried Wöber; Manuel Curto; Papius Tibihika; Paul Meulenbroek; Esayas Alemayehu; Lars Mehnen; Harald Meimberg; Peter Sykacek
Journal:  PLoS One       Date:  2021-04-15       Impact factor: 3.240

Review 2.  Machine Learning Techniques for the Prediction of B-Cell and T-Cell Epitopes as Potential Vaccine Targets with a Specific Focus on SARS-CoV-2 Pathogen: A Review.

Authors:  Syed Nisar Hussain Bukhari; Amit Jain; Ehtishamul Haq; Abolfazl Mehbodniya; Julian Webber
Journal:  Pathogens       Date:  2022-01-24

3.  AK-DL: A Shallow Neural Network Model for Diagnosing Actinic Keratosis with Better Performance Than Deep Neural Networks.

Authors:  Liyang Wang; Angxuan Chen; Yan Zhang; Xiaoya Wang; Yu Zhang; Qun Shen; Yong Xue
Journal:  Diagnostics (Basel)       Date:  2020-04-13
  3 in total

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