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Computational Medicine

The computational medicinal field encompasses the science and engineering, of using clinical and biological data, to develop state of the art algorithms and establish relations among various clinical and biological systems. This sophisticated scientific field has significantly improved current knowledge of medical and biological systems in order to individualize our treatment process. However, a large growing field with advanced and sensitive scientific profiling requires precise in-depth knowledge, expertise, and understanding otherwise these innovative solutions to the world's most pressing clinical challenges may be misdirected.

Magnetic Resonance Imaging (MRI) or Diffusion Tensor Imaging (DTI) can be used to produce 3D images of the brain. These are also the best medical imaging methods for the clinical study of brain, tissues, spinal cord, tendon, and ligament injuries. Multimodal brain imaging provides us with a noninvasive measurement of several neural disorders, including Parkinson's disease and depression. It can also enhance the clinical analysis and medical interventions of the neuropathological diagnosis process. Cardiac muscle is self-excitable and its regulatory mechanism is stimulated by the nervous system, its contraction process is similar to that of skeletal muscle. These automated actions of the cardiac muscles make leads to cardiac irregularities that best assessed by medical imaging and ECG.  Parkinson's disease is a chronic neurological disorder causing a person to be unable to control normal movement of the body. Medical imaging and behavioral gait analysis may improve the clinical understanding of this disease. A stem cell has a remarkable proliferation and self-renewal capacity and expresses molecular markers in response to tissue specific injuries/diseases. Computational modeling has the capability to enhance clinical studies on cell remodeling and the therapeutic process. Integrated image analysis of Positron Emission Tomography (PET) and Computed Tomography (CT) can provide a detailed sectional view of the brain, internal organs, and tissues.

The CyberDash CryptoMetrics is at the edge of innovation with the activities that include the development and evaluation of computational medicine, artificial/computational intelligence, data analytics, statistical theory, biosecurity, and bioethics which facilitate research with biomedicine and clinical data.   We work on cardiac disease, Parkinson's, neuropathology, medical imaging (MRI, DTI, CT, and PET), and computational cell biology. We designed computational model, establishing correlation among different types of data sets, implement stochastics theory to predict outcomes of the treatment. Our goal is to accelerate clinical trials by developing computational model with big data analytics and results interpretation. 

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