ICITS 2020 PROGRAM BOOK ORGANIZED BY FSTM KUIS

ITS 040_1 | DEEP LEARNING BASED EARLY PREDICTION SCHEME FOR BREAST CANCER
Deepak.R.U, N.Hemavathi, R.Sriranjani, A.Parvathy and M.Meenalochani
SASTRA Deemed to be University, India
[email protected]

Abstract. Breast cancer is one of the wide and fast spreading diseases among the younger age
groups of women. Further, for every four minutes, a woman is diagnosed whereas for every eight
minutes, a woman dies of breast cancer. Unfortunately, the detection of cancer is at later stage
and hence, the maximum lifetime that can be extended is five years. If the detection is at early
stage, then their lifetime could have been improved. Hence, the proposal aims at predicting the
presence of breast cancer at early stage through deep learning. Deep learning model is created in
python programming language by using keras Application Programmable Interface and the
accuracies of the popular machine learning models such as Logistic Regression, K Nearest
Neighbours, Support Vector Machine (linear), Support Vector Machine (RBF), Gaussian (NB),
Decision Tree and Random Forest are measured. The data set with 30 attributes are considered
initially and then feature selection is attained through heat map. The model consists of number of
hidden layers which performs binary classification on the given dataset to predict whether a person
is malignant or benign. The proposal exhibits its supremacy by demonstrating greater accuracy and
almost similar confusion matrix and execution time in prediction with reduced attributes obtained
through feature selection.

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ITS 040_2 | MACHINE LEARNING BASED VEHICLE HEALTH MONITORING SYSTEM
R.Janani, N.Hemavathi, M.Meenalochani, Sunkavalli Sai Chandana, Amrita Sona
Department of Electronics and Instrumentation Engineering, School of Electrical and Electronics

Engineering
SASTRA Deemed to be University, India

[email protected]
Abstract. Now-a-days, one of the issue that needs to be focused is road accidents due to poor
vehicle maintenance. Any thing that is used regularly should be checked after regular time period,
vehicles are no exception from it. Considering the busy lives, everyone tend to forget the vital things
such as taking the vehicle for service. The sensors are connected to various parts of the vehicle
such as steering, wheels and lights hold certain threshold value. Whenever any of these sensors
sense the deviation from threshold value, they notify the operator by sending alert messages to
the application in mobile phone using Node MCU and internet. Such Deviation can also be
predicted beforehand by implementing Machine learning using software like Matlab, Python etc.
These predictions can reduce the rate of road accidents that occur due to defects in the parts of
the vehicle.

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SPONSORSHIP
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