An Efficient Framework for Cryotherapy with Apriori based Probability Tree Classifier(APTC)

A. Kowshika , Dr. M. Gobi

Cryotherapy, warts, apriori, healing, location, patients,treatment

Machine-learning (ML) methods are applied in many different medical applications such as understanding the disease developments, diagnosing and choosing a treatment method. Machine-learning (ML) methods have the great importance when it applied interdisciplinary. Besides several areas, ML methods save cost factor and time in medical applications. In this study, we experimented several ML methods with different approaches on Cryotherapy dataset, which are applied on wart treatment. Apriori based Probability Tree Classifier (APTC) and naive bayes used to predicts if warts can be healed by the cryotherapy treatment.

Published Paper   E-Certificate

"An Efficient Framework for Cryotherapy with Apriori based Probability Tree Classifier(APTC)", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.4, Issue 10, page no.40 - 44, October-2019, Available :https://ijsdr.org/papers/IJSDR1910008.pdf

Volume 4 Issue 10, October-2019

Pages : 40 - 44

Paper Reg. ID: IJSDR_191037

Published Paper Id: IJSDR1910008

Downloads: 000347041

Research Area: Biological Science

Country: Thirupur, Tamilnadu, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1910008

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1910008

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition