Nada Al-Zahrani

Bio: Nada Al-Zahrani is an academic researcher from King Saud University. The author has contributed to research in topics: Knowledge extraction & Asthma. The author has an hindex of 2, co-authored 3 publications receiving 31 citations.

Mbreath: Asthma monitoring system on the go

Abstract: Prevalence of asthma, especially in air polluted areas, has dramatically increased. As a result, the demand for a system that is able to predict asthma attacks and monitor a patient's condition is becoming increasingly important. This paper presents a prototype system that allow asthma's patients to self-monitor their symptoms condition and manage their conditions accurately, as well as informing the medics in the case of emergency.

Multiple bleeding detection in wireless capsule endoscopy

Abstract: Wireless capsule endoscopy (WCE) is an emerging technology that aims to detect pathology in the patient gastrointestinal tract. Physicians can use WCE to detect various gastrointestinal diseases at early stages. However, the diagnosis is tedious because it requires reviewing hundreds of frames extracted from the captured video. This tedious task has promoted researchers’ efforts to propose automated diagnosis tools of WCE frames in order to detect symptoms of gastrointestinal diseases. In this paper, we propose an automatic multiple bleeding spots detection using WCE video. The proposed approach relies on two main components: (1) a feature extraction intended to capture the visual properties of the multiple bleeding spots, and (2) a supervised and unsupervised learning techniques which aim to accurately recognize multiple bleeding.

Data Analysis for Courses Registration

Abstract: Data mining is a knowledge discovery process to extract the interesting previously unknown, potentially useful and non-trivial patterns from large repositories of data. There is currently increasing interest in data mining in educational systems, making it into a growing new research community. This paper applies a frequent patterns extraction approach to analyzing the distribution of courses in universities, where there are core and elective courses. The system analyzes the data that is stored in the department's database. The objective is to consider if allocation of courses is appropriate when they are more likely to be taken in the same semester by most students. A workflow is proposed; where the data is assumed to be collected over many semesters for already graduated students. A case study is presented and results are summarized. The results show the importance of the proposed system to analyze the courses registration in a given department.

Smartphone and tablet self management apps for asthma

Abstract: Background Asthma is one of the most common long-term conditions worldwide, which places considerable pressure on patients, communities and health systems. The major international clinical guidelines now recommend the inclusion of self management programmes in the routine management of patients with asthma. These programmes have been associated with improved outcomes in patients with asthma. However, the implementation of self management programmes in clinical practice, and their uptake by patients, is still poor. Recent developments in mobile technology, such as smartphone and tablet computer apps, could help develop a platform for the delivery of self management interventions that are highly customisable, low-cost and easily accessible. Objectives To assess the effectiveness, cost-effectiveness and feasibility of using smartphone and tablet apps to facilitate the self management of individuals with asthma. Search methods We searched the Cochrane Airways Group Register (CAGR), the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, CINAHL, GlobalHealth Library, Compendex/Inspec/Referex, IEEEXplore, ACMDigital Library, CiteSeerx and CAB abstracts via Web of Knowledge. We also searched registers of current and ongoing trials and the grey literature. We checked the reference lists of all primary studies and review articles for additional references. We searched for studies published from 2000 onwards. The latest search was run in June 2013. Selection criteria We included parallel randomised controlled trials (RCTs) that compared self management interventions for patients with cliniciandiagnosed asthma delivered via smartphone apps to self management interventions delivered via traditional methods (e.g. paper-based asthma diaries). Data collection and analysis We used standard methods expected by the Cochrane Collaboration. Our primary outcomes were symptom scores; frequency of healthcare visits due to asthma exacerbations or complications and health-related quality of life. Main results We included two RCTs with a total of 408 participants. We found no cluster RCTs, controlled before and after studies or interrupted time series studies that met the inclusion criteria for this systematic review. Both RCTs evaluated the effect of a mobile phone-based asthma self management intervention on asthma control by comparing it to traditional, paper-based asthma self management. One study allowed participants to keep daily entries of their asthma symptoms, asthma medication usage, peak flow readings and peak flow variability on their mobile phone, from which their level of asthma control was calculated remotely and displayed together with the corresponding asthma self management recommendations. In the other study, participants recorded the same readings twice daily, and they received immediate selfmanagement feedback in the form of a three-colour traffic light display on their phones. Participants falling into the amber zone of their action plan twice, or into the red zone once, received a phone call from an asthma nurse who enquired about the reasons for their uncontrolled asthma. We did not conduct a meta-analysis of the data extracted due to the considerable degree of heterogeneity between these studies. Instead we adopted a narrative synthesis approach. Overall, the results were inconclusive and we judged the evidence to have a GRADE rating of low quality because further evidence is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. In addition, there was not enough information in one of the included studies to assess the risk of bias for themajority of the domains. Although the other included study was methodologically rigorous, it was not possible to blind participants or personnel in the study. Moreover, there are concerns in both studies in relation to attrition bias and other sources of bias. One study showed that the use of a smartphone app for the delivery of an asthma self management programme had no statistically significant effect on asthma symptom scores (mean difference (MD) 0.01, 95% confidence interval (CI) -0.23 to 0.25), asthma-related quality of life (MD of mean scores 0.02, 95% CI -0.35 to 0.39), unscheduled visits to the emergency department (OR 7.20, 95% CI 0.37 to 140.76) or frequency of hospital admissions (odds ratio (OR) 3.07, 95% CI 0.32 to 29.83). The other included study found that the use of a smartphone app resulted in higher asthma-related quality of life scores at six-month follow-up (MD5.50, 95%CI 1.48 to 9.52 for the physical component score of the SF-12 questionnaire; MD 6.00, 95% CI 2.51 to 9.49 for the mental component score of the SF-12 questionnaire), improved lung function (PEFR) at four (MD 27.80, 95% CI 4.51 to 51.09), five (MD 31.40, 95% CI 8.51 to 54.29) and six months (MD 39.20, 95% CI 16.58 to 61.82), and reduced visits to the emergency department due to asthmarelated complications (OR 0.20, 95% CI 0.04 to 0.99). Both studies failed to find any statistical differences in terms of adherence to the intervention and occurrence of other asthma-related complications. Authors’ conclusions The current evidence base is not sufficient to advise clinical practitioners, policy-makers and the general public with regards to the use of smartphone and tablet computer apps for the delivery of asthma selfmanagement programmes. In order to understand the efficacy of apps as standalone interventions, future research should attempt to minimise the differential clinical management of patients between control and intervention groups. Those studies evaluating apps as part of complex, multicomponent interventions, should attempt to tease out the relative contribution of each intervention component. Consideration of the theoretical constructs used to inform the development of the intervention would help to achieve this goal. Finally, researchers should also take into account: the role of ancillary components in moderating the observed effects, the seasonal nature of asthma and long-term adherence to self management practices.

NeuroPlace: Categorizing urban places according to mental states

Abstract: Urban spaces have a great impact on how people’s emotion and behaviour. There are number of factors that impact our brain responses to a space. This paper presents a novel urban place recommendation approach, that is based on modelling in-situ EEG data. The research investigations leverages on newly affordable Electroencephalogram (EEG) headsets, which has the capability to sense mental states such as meditation and attention levels. These emerging devices have been utilized in understanding how human brains are affected by the surrounding built environments and natural spaces. In this paper, mobile EEG headsets have been used to detect mental states at different types of urban places. By analysing and modelling brain activity data, we were able to classify three different places according to the mental state signature of the users, and create an association map to guide and recommend people to therapeutic places that lessen brain fatigue and increase mental rejuvenation. Our mental states classifier has achieved accuracy of (%90.8). NeuroPlace breaks new ground not only as a mobile ubiquitous brain monitoring system for urban computing, but also as a system that can advise urban planners on the impact of specific urban planning policies and structures. We present and discuss the challenges in making our initial prototype more practical, robust, and reliable as part of our on-going research. In addition, we present some enabling applications using the proposed architecture.

E-Health status in Saudi Arabia: a review of current literature

Abstract: Due to recent and growing interest in e-health initiatives in Saudi Arabia, improving the state of knowledge pertaining to current e-health programs, initiatives, and efforts is of critical importance to academics, clinicians, and policy makers. In this research review the literature on specific applications of e-health in Saudi Arabia is considered, including studies investigating Electronic Health Records (EHR), Electronic Medical Records (EMR), studies investigating Computerized Provider Order Entry (CPOE) and Clinical Decision Support Systems (CDSS). Moreover, this paper explores studies on telemedicine, mobile health, and other e-health applications. The findings reveal evidence that e-health in Saudi Arabia is growing as many organizational and individual initiatives have implemented e-health applications. However, the number of studies available about e-health in Saudi Arabia remains low. Data is limited to a few organizations and does not necessarily reflect the breadth and depth of the current and potential use of e-health for healthcare organizations in the region.