Real time data analysis and visualization for the breast cancer disease

Today, the amount of data that are digitally collected in the healthcare sector is tremendous and expanding rapidly, these data are inherently geospatial and temporal ranging from individual families to whole states and from minutes to decades. Therefore, they need sophisticated data management and analysis to be transformed into valuable knowledge. Healthcare professionals are faced with several challenges regarding extracting knowledge from this massive amount of data in order to support the decision-making process. To gain advantage of health care big data, big data analytics need to be exploited to utilize and understand patterns associations within these data thus make the right decision. In this research, an interactive data analysis and visualization tool is proposed to visually compare the performance of three machine learning algorithms on Wisconsin Diagnostic Breast Cancer (WDBC) dataset. The proposed model consists of two phases: input phase and analysis/visualization phase. It aims to allow the user to interactively compare the performance of three different ML algorithms (KNN, SVM and NB) in terms of accuracy, sensitivity and error rate in a user-friendly way. Here, SVM classifier has proven its efficiency and it is concluded as the best classifier with the highest accuracy as compared to the other two classifiers

MANAGEMENT AND ASSESSMENT OF DEHYDRATION IN PEDIATRICS

The level of fluid deficit may be difficult to scientifically quantify and there is no laboratory worth that is either delicate or details to approximate the degree of dehydration in children. Rehydration may take place by means of oral, subcutaneous, or IV paths. We performed a search using electronic databases; MEDLINE, science-direct, and EMBASE, through October, 2018. Dehydration related to gastroenteritis makes up a considerable worry of disease worldwide. Most of dehydration is amenable to ORT; only the treatment of severe dehydration needs IVF. Prior pilot data on the superiority of rapid IVF administration for rehydration has actually been refuted. Nevertheless, a new research suggests that initial rehydration with glucose including IVF trends toward lowering the return visits and decreasing the admission rates. More data on the efficiency and safety and security of antiemetics has actually been produced. Antiemetics have been proven well tolerated without masking severe alternate diagnoses, efficacious in improving the success of ORT, and affordable. These brand-new data supporters highly for the consolidation of antiemetics right into the scientific guidelines. Variability in guideline conformity has been shown, with doctors mentioning troubles in evaluating dehydration and scientific judgment as factors for variation

“Not everyone can use Git”: Research Software Engineers’ recommendations for scientist-centred software support (and what researchers really think of them)

Research Software Engineers (RSEs) are at the coalface of ensuring that computational science is accurate, reliable and reproducible, and their views on making progress in this domain are therefore particularly valuable. This is not always recognized by the scientific community, however: work examining the challenge of developing research software tends to focus on the views of academics, and RSEs’ voices are rarely found in the evidence base. We report the results of a project that brings together researchers and RSEs, to determine how to help scientists publish their code. We interview scientists to identify challenges, and we interview RSEs to determine how to overcome them. We formalize the results into a set of recommendations, and evaluate them in a survey completed by 65 computational scientists. The survey shows that improving tool GUIs, linking internal repositories to external ones, and training in version control would all aid scientists in publishing reliable code. It also demonstrates that RSEs' views are valued by researchers: every recommendation received strong support. We conclude that RSEs can play a crucial role in scientific software policy, and their expertise should be officially recognized. Paper available at: https://www.research.manchester.ac.uk/portal/en/publications/not-everyone-can-use-git-research-software-engineers-recommendations-for-scientistcentred-software-support-and-what-researchers-really-think-of-them(669fd8be-f87e-479f-8f8d-da9e1af4f26c).htm