Health Informatics
Areas of Research
Breast Cancer Detection
Breast cancer is the most common type of cancer affecting women worldwide. Various researchers have proposed methods and tools based on Machine Learning and Convolutional Neural Networks for assessing mammographic images, but these methods have produced detection and interpretation errors resulting in false-positive and false-negative cases. This problem can potentially be resolved by implementing effective image pre-processing techniques to create training data for Deep-CNN.
Prediction of Cardiovascular Disease
Cardiovascular diseases (CVD) are among the most common serious illnesses affecting human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce mortality rates. Identifying risk factors using machine learning models is a promising approach. This research aims to build a model incorporating deep learning architecture to achieve effective prediction of heart disease.
Privacy and Security Issues in Electronic Health Record
Digital transformation has led to the conception of electronic health record (EHR) which has helped improve ways to care for people. However, carrying out this change did not go effortlessly due to privacy and security issues. This research aims to find ways in improving the privacy and security of health data.
Projects
Processing of Breast Cancer Images to Create Datasets for Deep-CNN
Classification of Enhanced Mammogram Images using D-CNN, C-ReLU and AM-SoftMax Functions
Classification of Cancers using Nuclei segmentation
Deep Learning Algorithms in the Effective Prediction of Breast Cancer
Application of Privacy by Design Mechanisms to Safeguard Personal Data in Patient Record Management System
