MRI based medical image analysis: Survey on brain tumor grade classification

Cloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an “OMICS-context”, e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain.

https://link.springer.com/content/pdf/10.1186%2Fs12911-015-0145-7.pdf

A scoping review of cloud computing in healthcare

The new and ground-breaking real-time remote monitoring in triage and priority-based sensor technology used in telemedicine have significantly bounded and dispersed communication components. To examine these technologies and provide researchers with a clear vision of this area, we must first be aware of the utilised approaches and existing limitations in this line of research. To this end, an extensive search was conducted to find articles dealing with (a) telemedicine, (b) triage, (c) priority and (d) sensor; (e) comprehensively review related applications and establish the coherent taxonomy of these articles. ScienceDirect, IEEE Xplore and Web of Science databases were checked for articles on triage and priority-based sensor technology in telemedicine. The retrieved articles were filtered according to the type of telemedicine technology explored. A total of 150 articles were selected and classified into two categories. The first category includes reviews and surveys of triage and priority-based sensor technology in telemedicine. The second category includes articles on the three-tiered architecture of telemedicine. Tier 1 represents the users. Sensors acquire the vital signs of the users and send them to Tier 2, which is the personal gateway that uses local area network protocols or wireless body area network. Medical data are sent from Tier 2 to Tier 3, which is the healthcare provider in medical institutes. Then, the motivation for using triage and priority-based sensor technology in telemedicine, the issues related to the obstruction of its application and the development and utilisation of telemedicine are examined on the basis of the findings presented in the literature.

/pdf/systematic-review-of-real-time-remote-health-monitoring-9sy5ksfwue.pdf

Systematic Review of Real-time Remote Health Monitoring System in Triage and Priority-Based Sensor Technology: Taxonomy, Open Challenges, Motivation and Recommendations

Remotely monitoring a patient's condition is a serious issue and must be addressed. Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies, methods and installations that enable doctors or other medical professionals to work remotely to consult, diagnose and treat patients. The goal of RHMS is to provide timely medical services at remote areas through telecommunication technologies. Through major advancements in technology, particularly in wireless networking, cloud computing and data storage, RHMS is becoming a feasible aspect of modern medicine. RHMS for the prioritisation of patients with multiple chronic diseases (MCDs) plays an important role in sustainably providing high-quality healthcare services. Further investigations are required to highlight the limitations of the prioritisation of patients with MCDs over a telemedicine environment. This study introduces a comprehensive and inclusive review on the prioritisation of patients with MCDs in telemedicine applications. Furthermore, it presents the challenges and open issues regarding patient prioritisation in telemedicine. The findings of this study are as follows: (1) The limitations and problems of existing patients' prioritisation with MCDs are presented and emphasised. (2) Based on the analysis of the academic literature, an accurate solution for remote prioritisation in a large scale of patients with MCDs was not presented. (3) There is an essential need to produce a new multiple-criteria decision-making theory to address the current problems in the prioritisation of patients with MCDs.

/pdf/real-time-remote-health-monitoring-systems-a-review-on-45q99p4iz8.pdf

Real-Time Remote-Health Monitoring Systems: a Review on Patients Prioritisation for Multiple-Chronic Diseases, Taxonomy Analysis, Concerns and Solution Procedure.

Transfer learning for medical images analyses: A survey

Objectives
The existing processes of health care systems where data collection requires a great deal of labor with high-end tasks to retrieve and analyze information, are usually slow, tedious, and error prone, which restrains their clinical diagnostic and monitoring capabilities. Research is now focused on integrating cloud services with P2P JXTA to identify systematic dynamic process for emergency health care systems. The proposal is based on the concepts of a community cloud for preventative medicine, to help promote a healthy rural community. We investigate the approaches of patient health monitoring, emergency care, and an ambulance alert alarm (AAA) under mobile cloud-based telecare or community cloud controller systems.

Dynamic Integration of Mobile JXTA with Cloud Computing for Emergency Rural Public Health Care.

Internet use, especially social media has dramatically changed the way adolescents communicate, socialize, make and maintain friendships. Internet Addiction Disorder (IAD) is generally defined as an uncontrollable desire to use the Internet, leading to acute nervousness and aggression in the event of deprivation and progressive deterioration of social life. IAD is becoming a common mental health problem in adolescents. Worldwide, the prevalence of IAD in adolescents may vary from 1.98% to 35.8%. Sadness, feeling down, having a loss of interest in daily activities are some of the symptoms of IAD. Some possible treatments of IAD includes doing sport or spending more time with friends and developing healthy social networks.

https://www.longdom.org/open-access/internet-addiction-disorder-and-mental-health-in-adolescents.pdf

Internet Addiction Disorder and Mental Health in Adolescents

In medical diagnosis, the functional and structural information of the brain as well as the impending abnormal tissues is very crucial and important with an MR image. A collective CAD system that detects and classifies the brain tumor by exploiting the structural information is presented. Magnetic Resonance Imaging (MRI) T1-weighted and T2-weighted images provides suitable variation of contrast between the different soft tissues of the brain which is suitable for detecting the brain tumor. Both the Magnetic Resonance (MR) image sequences are composited using the alpha blending technique. The tumor area in the MR images will be segmented using the Enhanced Watershed Segmentation (EWATS) algorithm. The feature extraction is a means of signifying the raw image data in its abridged form to ease the classification in a better way. An expert classification assistant is tried out to help the physicians to classify the detected MRI brain tumor in an efficient manner. The proposed method uses the Regularized Logistic Regression (RLR) for the efficient cataloguing of brain tumor in which it achieves an effective accuracy rate of 96%, specificity rate of 86% and sensitivity rate of 97%.

T1-t2 weighted mr image composition and cataloguing of brain tumor using regularized logistic regression

Objectives
Mobile JXTA (Juxtapose) gaining momentum and has attracted the interest of doctors and patients through P2P service that transmits messages. Audio and video can also be transmitted through JXTA. The use of mobile streaming mechanism with the support of mobile hospital management and healthcare system would enable better interaction between doctors, nurses, and the hospital. Experimental results demonstrate good performance in comparison with conventional systems. This study evaluates P2P JXTA/JXME (JXTA functionality to MIDP devices.) which facilitates peer-to-peer application+ using mobile-constraint devices. Also a proven learning algorithm was used to automatically send and process sorted patient data to nurses.

JXTA: A Technology Facilitating Mobile P2P Health Management System

Objectives: In recent years, we have tremendous growth of users in Online Social Networks (OSN) such as Facebook, Google+, twitter etc. This becomes major reason for enabling web as largest market defining E-Commerce. Many companies use OSN as their sales channel as they can reduce operating cost for managing orders significantly compared with traditional channels. Also viral marketing is very popular in OSN. But the major drawback of this channel is if the company doesn’t satisfy the customer, then the same OSN can rapidly propagate a bad reputation of the company affecting the company’s business. Hence for customers it has become very important to identify and filter dishonest recommenders. So it becomes very important to recommend right items to right customers. In this survey, we aim to give a comprehensive review of research related to E-Commerce in OSN. Methods: First, we discuss web usage mining techniques for better shopping websites to satisfy customers. Also we discuss web mining techniques to find dishonest recommenders in OSN. Findings/ Improvements: Our survey explores the existing research highlights and also presents various researches in these topics. Also, we propose recommendation system which uses Semantic Web Mining process integrated with domain ontology which can be used to extract interesting patterns from, complex and heterogeneous data.

Survey on Web Mining Techniques and challenges of E-Commerce in Online Social Networks

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