Identification and Classification using Deep Learning Methods for Diagnosis of Mastocytosis: A Systematic Review

Resumen

Learning methods for detection and elucidation of mastocytosis is a novel research area.
Researchers urge their interest in developing new algorithms, artificial intelligence
frameworks and neural network architectures for analyzing the microscopic-imagery, microcirculations and spread of mast cells in various parts of the subjects. In this article evidences
related to the detection and diagnosis of mastocytosis are collected, synthesized and
evaluated. Publications related to mastocytosis and deep learning in recent years in IEEE,
ScienceDirect and Others were classified and collected, which includes 182 articles using
traditional methods out of which 82 are biological foundations of mastocytosis. A systematic
literature review has been conducted with relevant criteria.