Understanding disease progression and comorbidities using multi-omics and clinical information
Summary
This research project aims at exploring clinical and multi-omics data to improve our present understanding of disease progression, transition and comorbidities. To achieve this aim, this project will use techniques, methods and models from Big data analytics, Complex networks and Machine learning.
Supervisor(s)
Research Location
Program Type
PHD
Synopsis
Many of the diseases do not develop alone in the human body. Instead, they lead to the development of other diseases in the long term. This negatively affects many quality measures of human life, including cost and life expectancy. Understanding disease progression, associated transitions and comorbidities can help healthcare policymakers and related stakeholders to take appropriate preventive actions, which will eventually reduce treatment cost and improve quality of life. On the other side, disease information regarding multi-omics and clinical information has recently gained wide attention for research investigation purposes. Using techniques, methods and models from Big data analytics, Complex networks and Machine learning, this project will build diseasome and comorbidity maps to have a better understanding of disease progression and transition.
Additional Information
- Use of research technique / methodology / technology
- Eligibility criteria / candidate profile
Want to find out more?
Contact us to find out what’s involved in applying for a PhD. Domestic students and International students
Contact Research Expert to find out more about participating in this opportunity.
Browse for other opportunities within the Project Management .
Keywords
Disease progression; Disease transition; Big data analytics; Diseasome and Comorbidities
Opportunity ID
The opportunity ID for this research opportunity is: 2469
Other opportunities with Dr Shahadat Uddin