3 / 7
Page 42
Notes:
Joint Event
November 29-30, 2019 | Frankfurt, Germany
28
th
International Conference on
3
rd
International Conference on
Diabetes and Endocrinology
Diabetes and Metabolism
&
2
0
1
9
CONGRESS
DIABETES
2019
DIABETES
Journal of Diabetology | Volume 3
Hybrid approach by using Hybrid-TBP for Tuberculosis drug resistance analysis
Maji S
DIT University, India
T
imely correct and rapid prediction of Mycobacterium
tuberculosis (MTB) resistance against available
tuberculosis (TB) drugs is crucial for control and management
of the TB. Various machine learning methods have been
largely applied for timely predicting resistance of MTB given a
specific drug and identifying resistancemarkers. Even though,
they are not properly validated in the large group of MTB
samples across the globe in terms of resistance prediction
and resistance marker identification.
Our proposed Hybrid Machine technique named Hybrid-
TBP can be used for the identification of Mycobacterium
tuberculosis (MTB) resistance beside numerous existing TB
drugs for the management and control of TB. In this hybrid
machine learning tool initial data samples of MTB data
samples is provided to the Principle Component Analysis
(PCA) for feature selection and classification is performed for
result generation by using Support Vector Machine (SVM)
with polynomial kernel. This Hybrid-TBP can be utilized as
a supporting software tools in the field of medical science
for MTB resistance. As compared to other existing available
software MTB prediction tools, this proposed technique gives
better performance.
Speaker Biography
Maji S has completed her PhD from Thapar University, India in the year
2013. She is presently working as the Assistant professor at DIT University,
Dehradun, India. She has large number of publications that have been cited
over 60 times, and his/her publication H-index is 5 and has been serving as
a reviewer of reputed Journals.
e:
srabantiindia@gmail.com