Pushing the Limits of Data Scientist’s Toolbox for Clinical Data Analytics
Data analytics can be, and has been, widely used in the healthcare sector and services. With many institutions adopting Electronic Health Records, enormous amounts of data are becoming available that, if mined correctly, can reveal hidden knowledge and provide useful insights to many stakeholders. Medical data mining can tackle issues such as identification of high risk patients, prediction of treatment outcome, early diagnosis, etc. In this presentation we address the special challenges that projects addressing clinical data mining objectives would face that are not classically faced in other types of data analytics projects. We present some findings from our work on the project "Understanding Cancer Therapy Effectiveness: Personalized Treatment Guidelines using Data Analytics", and propose methods and techniques that can help to improve the outcome of available tools and algorithms for better usable findings that can be adopted in the healthcare field.
Dr. Asem Kasem obtained his Doctor of Computer Science degree from University of Tsukuba, Japan, in 2011. He has since worked in different higher education institutions in South East Asia and the Middle East. He is currently an Assistant Professor in Universiti Teknologi Brunei (UTB), and his main area of expertise is in Intelligent Systems and Data Mining. Among his recent projects is the work on understand cancer therapy effectiveness using data analytics, as an FRGS project collaborating APU, UTB, Tokushima University, and Malaysia’s Institute for Medical Research.
Hema Latha Krishna Nair is Senior Lecturer of Faculty of Information Technology & Science INTI International University, who has been working in education since 2008. In the past she had been leading and teaching modules such as Database programming, Artificial Intelligence Methods and Knowledge Discovery and Data Analytics. During 2002-2008, she was working as Software Engineer and served at Panasonic AVC (M) Sdn Bhd under the Research and Development department working on embedded programing and actively involved in Software Quality Assurance for CCMI Level 3. She achieved her Bachelor’s Degree in Computer Science from Universiti Sains Malaysia in 2002 and further pursued her Master’s Degree in Information technology Management from Universiti Teknologi Malaysia in 2004 submitting industrial prototype dissertation on Data Analytics for a Manufacturing company and currently pursuing her Phd in Software Engineering at Universiti Teknologi Malaysia. Hema Latha was actively involved in research on Flood Mitigation and Water Channeling and has been awarded the Project Lead for the Ministry of Education Prototype Research Grant in 2014 for special Grant under Malaysian Disaster Management. Currently she is the co-researcher of Fundamental Research Grant from Ministry of Higher Education for Cancer Data Analytics Malaysia. She is an active member of Big Data Malaysia and Persatuan Data Sains Malaysia.