A large number of patients in Pakistan suffer dire consequences due to incorrect or late diagnosis, misinterpretation of clinical findings, inter-observer variability amongst the medical practitioners and lack of specialists in remote areas. Developing novel computational methods to automate diagnosis can significantly reduce the errors, address the issue of scarcity of medical Capturemanpower and result in improved outcomes for the patient and saving thousands of lives. Secure internetworking of hospitals for sharing of patients’ clinical and image data, telemedicine, image guided surgery, classification of biomarkers for cancer screening, reducing comorbidities from diabetes, automated medical image analysis, wearable health monitors and robotic support for old age patients are some areas where active research yields plausible results. Some of the research areas include:

 

  • Classification of serum biomarkers for prediction of cardiovascular diseases and cancer.
  • Analysis of images and biomarkers for assessment of treatment regimen such as pre- and post-chemotherapy in cancer.
  • Medical image analysis for early detection of pathologies such as breast cancer, bone cancer, myocardial abnormalities.
  • Medical image registration for assessing disease progression and image guided surgery etc.
  • Integration of wearable health monitoring devices with centralized database for disease risk group identification.
  • Automated monitoring of elderly patients and dispatch of emergency services.
  • Robotic assistance for elderly patients in performing daily tasks.
  • Automated diagnosis in the emergency department for more precise management of patients.
  • Classification of Electroencephalograms (EEG) for prediction of brain growth abnormalities.
  • Classification of Electroencephalograms (EEG) for human computer interaction (HCI).
  • Automated monitoring of lifestyle and correlation to disease prevalence and progression.
  • Digitization of patient data for electronic healthcare records.

 

The aims of the centre are as follows:

 

  • Centre has initiated state-of-the-art informatics research for improving public health practices across a number of methodological disciplines, particularly health informatics, bioinformatics, biostatistics, machine learning, computer vision, computer science and software engineering.
  • Focus of the research is on development of intelligent systems to support evidence-based healthcare and developing methodologies for utilizing IT and communication to improve the quality of health care.
  • The Centre is an applied research and research-led training environment for problem-solving across disciplines and developing complex models of disease prediction and progression, classification of risk groups and lifestyle intervention supported with hardware and software platforms.
  • The Centre provides an e-infrastructure for health research, connecting a rich variety of investigators (clinical, public health and health services, computer scientists and engineers) with relevant analytical and modeling tools and large-scale aggregations of data, to establish broad-range medical applications.

 

A tentative list of PhD projects:                    

 

  1. Non-invasive assessment of fracture healing in long bones using acoustic conduction.
  2. Non-invasive estimation of bone density in osteoporotic patients using acoustic conduction.
  3. Non-invasive estimation of intra-ocular pressure.
  4. Automatic assessment and quantification of haematomas in traumatic brain injury patients.
  5. Estimation of myocardial thickness in CT thorax.
  6. Detection and quantification of arrhythmia using pulse oximeter.

 

Research Objectives:

This centre will provide solutions for prediction and progression of diseases and automated analyses of medical images through a colligation of clinicians and computer scientists.

Expected Research Deliverables:

  1. Research publications in conferences and journals.
  2. Collaboration with leading hospitals for healthcare research.
  3. Commercial Electronic Healthcare software (and supporting hardware).

 

Expected effect on Undergraduate Students:

The involvement of undergraduate students in the process will improve the quality of their final year projects and also equip them with the knowledge, skills and attitude which are necessary to excel in professional life.