Overview Of Manifold Learning And Its Application In Medical Data Set
Elnaz Golchin · Zenodo (CERN European Organization for Nuclear Research) · 2014
ABSTRACT: The purpose of this study is introduction of new and efficient applications of manifold learning in medical Science and related sciences. Manifold learning is one of the most widely used methods in precise clustering of high-volume data set in data analysis science.In the first; we have a short overview on definition of manifold learning and its main algorithms. Then we describe how to use these algorithms in data mining. In its applications can be cited to database classification of tiny cancer, evaluation of biological pathways of gene ontology, predict brain tumour progression, cage base modelling for all of body movement in the biomechanical science and also processing of brain and heart images. In the following we will describe some of these applications in details.