Intelligent Medical Decision Support

(a) Assessment of the risk of stroke based on ultrasound images and clinical data
Carotid plaques have been associated with ipsilateral neurological symptoms. High-resolution ultrasound can provide information not only on the degree of carotid artery stenosis but also on the characteristics of the arterial wall including the size and consistency of atherosclerotic plaques. The aim of this study is to determine whether the addition of ultrasonic plaque texture features to clinical features in patients with asymptomatic internal carotid artery stenosis (ACS) improves the ability to identify plaques that will produce stroke. 

(b) MRI Image Analysis in Multiple Sclerosis Subjects for the prognosis of future disability
This study investigates the application of classification methods for the prognosis of future disability on MRI-detectable brain white matter lesions in subjects diagnosed with clinical isolated syndrome (CIS) of multiple sclerosis (MS).

In addition to this work a tool that helps clinicians work on MRI images has been created. This tool enables preprocessing of images / standardisation while it also enables the selection of plaques and other areas from the images in order to help the effort of creating an automated system to predict future disability.

(c) Diagnosis of children with acute abdominal pain
This research work involve the development of novel pattern recognition models based on the algorithmic theory of randomness and the application of these models to the problem of medical diagnosis. More specifically, a tool will be created for the diagnosis of illnesses in children suffering from acute abdominal pain. This application field is considered as extremely important, since wrong diagnoses for this problem can result in devastating consequences (even to death). More info on a research project called aspida based on this area can be found at: http://www.fit.ac.cy/research/aspida/en/index.html).

(d) Osteoporosis risk assessment
This work focus on the development of novel pattern recognition models based on the theory of Venn prediction and on the application of these models to the problem of osteoporosis risk assessment. The research will be based on real data that will be collected at several medical centers in Cyprus and Greece. More specifically a decision support tool will be developed to help clinicians identify individuals who are at increased risk of having osteoporosis and should therefore undergo further testing with a dual-energy X-ray (DEXA) scan for measuring their bone density. This application area is considered as extremely important since early detection of osteoporosis is vital for the prevention of osteoporotic fractures, which are associated with increased morbidity and mortality and high socio-economic costs. More info on a research project based on this area can be found at:  http://www.fit.ac.cy//research/osteoporosis/index.php