A World Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It is of critical importance that cancer be detected earlier so that many of these lives can be saved. Cancer grading is an important aspect for targeted therapy. As cancer diagnosis is highly invasive, time consuming and expensive, there is an immediate requirement to develop a non-invasive, cost-effective and efficient tools for brain cancer characterization and grade estimation. Brain scans using magnetic resonance imaging (MRI), computed tomography (CT), as well as other imaging modalities, are fast and safer methods for tumor detection. In this paper, we tried to summarize the pathophysiology of brain cancer, imaging modalities of brain cancer and automatic computer assisted methods for brain cancer characterization in a machine and deep learning paradigm. Another objective of this paper is to find the current issues in existing engineering methods and also project a future paradigm. Further, we have highlighted the relationship between brain cancer and other brain disorders like stroke, Alzheimer’s, Parkinson’s, and Wilson’s disease, leukoriaosis, and other neurological disorders in the context of machine learning and the deep learning paradigm.
Klebsiella are one among the group of gram negative rod shaped bacilli of family Enterobacteriaceae. Klebsiella are normal inhabitants of the intestinal tract of humans, animals, and environment. Klebsiella pneumoniae subspecies pneumoniae a most common gram negative lactose fermenting non motile, aerobic rod shaped bacilli, is second most common next to E. coli. They are facultative anaerobic bacterial vegetation of digestive tract of man and normal medical clinic procured pathogen, causing urinary tract contamination, nosocomial pneumonia and intra-stomach disease. Disease brought about by multidrug safe gram negative bacilli that produce broadened range beta-lactamase (ESBL) proteins have been accounted for with expanding recurrence in escalated care units related with noteworthy grimness and mortality.
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