Pooja Khurana
Manav Rachna International Institute of Research and Studies, India
Scientific Tracks Abstracts: J AIDS Clin Res
Alzheimer is a step wise and progressive neurodegenerative disorder caused by neuronal cell death. The predictable changes within the brain due to AD usually turn out almost two decades prior to the emergence of symptoms. This slightest phase of symptoms offers a great chance for therapeutic potential which can be directed to predict the progression of clinical AD. Mild cognitive impairment is the stage before AD. The transformation from MCI to AD has been of agreeable interest for the analysis of biomarkers that are beneficial for early AD detection. Determination of causative agents is a necessary step for the understanding and to figure out the effective treatment of a disease. Viruses are such agents that are responsible for the characteristic features of AD in the patients. The assessment of significant biomarkers can be overriding for the prompt pre-clinical diagnosis, therapeutics, examining and treatment, monitoring, and continuing phases of AD analysis, for that graph theoretical measures can be utilized to infer neurobiological mechanisms leading to loss of cognitive functions, behavioural and other brain disorders. Also, complex networks of brain can be well characterized by graph functions that distinguish Alzheimer brain from the normal ones. This paper highlights the studies for the viruses that along with the other genetic factors lead to AD and role of graph theory as an emerging tool for the early diagnosis of AD.
Pooja Khurana is a professional academician with strong analytical skills seeking the position of Associate professor and researcher focusing in Biomathematical modeling (epidemiological modeling). She has published multiple papers in the areas of biomathematics, social networking indexed in Scopus, Web of Science; presented various mathematical reports in conferences and seminars. She is an expert in applying mathematical principles to complex real-world problems and well-versed with mathematical software such as Mathematica, MATLAB. She is currently mentoring three scholar candidates and is skilled with applying the concepts of statistics, numerical analysis, and probability in building and simulation of mathematical models for improving healthcare.
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