The diagnosis of brain tumours has sparked attention in several research fields recently. Since the human body has anatomical structure by nature, finding brain tumours is an extremely laborious and time-consuming task. Cells develop quickly and uncontrollably, which causes brain tumours. It may cause death if not addressed in the beginning stages. Although there have been many substantial efforts and encouraging results in this field, precise segmentation and classification remain difficult tasks. Because of the variability in tumour location, shape, and size, detecting brain tumours is a significant difficulty. One of the most crucial problems with artificial intelligence systems is medical diagnostics using image processing and machine learning. Magnetic resonance imaging (MRI) is one of the technologies frequently used to find tumours in the brain (MRI). It provides crucial details that are employed in the process of carefully scanning the internal organisation of the human body. The variety and intricacy of brain tumours make it difficult to classify MR images. Sigma sifting, versatile limit, and detection locale are a portion of the cycles in the recommended technique for finding a brain cancer in MR pictures.
Introduction: Stem cells have the ability to build every tissue in thehuman body. Hence, they have great potential for futuretherapeutic uses in tissue regeneration and repair.Umbilical Cord Blood also contains stemcells that can differentiate into other types, such ascartilage, fat, hepatic, cardiac, and neural cells. Aim: This study was conducted to assess the knowledge and awareness about stem cells and its sources among Undergraduate and postgraduate students. Material And Methods: A cross sectional questionnaire based study was carried out among postgraduate andundergraduate medical and allied students of the medical college for a period of six months regarding knowledge and awarenessabout Stem Cells and its sources. Results: This study included 300 participants. Data from this study revealed a high level of awareness and knowledge of the stem cells among the undergraduate and postgraduate students. Conclusion: Our results showed excellent knowledge about sources of stem cell among the medical and para medical students.
Background: Biochemistry being considered as one of the fundamental science subjects taught during the first year of medical course, is proposed to be taught in the right perspective to medical students; since it forms the basic for General Medicine. Innovative curriculum with case-based learning is proven to develop the academic performance of biochemistry in medical students. Objective: To study the impact of manual and automated technique practicals on students' knowledge, skills, and attitude and its perception by the students. Materials and Methods: The 150 voluntary participants were first-year MBBS students who consented to undergo study. They were asked to perform practical of estimation of urinary sugar using Uristik and using Benedict's test (manual method). Knowledge was tested by questionnaire. Result: Statistically significant difference was found between automated method when compared with manual method. Conclusion: From this study, we found early clinical exposure to automated method was better than traditional manual method for medical students in Indian scenario. However, it was also noted that automated method requires extra efforts by the students to learn the accurate interpretation of the results. But, students were satisfied more by automated method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.