Data mining traditional Chinese medicine (TCM) lessons learnt from mining in law and allopathic medicine

Key decisions at the collection, pre-processing, transformation, mining and interpretation phase of any knowledge discovery from database (KDD) process depend heavily on assumptions and theorectical perspectives relating to the type of task to be performed and characteristics of data sourced. In this article, we compare and contrast theoretical perspectives and assumptions taken in data mining exercises in the legal domain with those adopted in data mining in TCM and allopathic medicine. The juxtaposition results in insights for the application of KDD for Traditional Chinese Medicine.

Aromatherapy for treatment of postoperative nausea and vomiting

Background: Postoperative nausea and vomiting is a common and unpleasant phenomenon and current therapies are not always effective for all patients. Aromatherapy has been suggested as a possible addition to the available treatment strategies. Objectives: This review sought to establish what effect the use of aromatherapy has on the severity and duration of established postoperative nausea and vomiting and whether aromatherapy can be used with safety and clinical effectiveness comparable to standard pharmacological treatments. Search methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2011, Issue 3); MEDLINE; EMBASE; CINAHL; CAM on PubMed; Meditext; LILACS database; and ISI Web of Science as well as grey literature sources and the reference lists of retrieved articles. We conducted database searches up to August 2011. Selection criteria: We included all randomized controlled trials (RCTs) and controlled clinical trials (CCTs) where aromatherapy was used to treat postoperative nausea and vomiting. Interventions were all types of aromatherapy. Aromatherapy was defined as the inhalation of the vapours of any substance for the purposes of a therapeutic benefit. Primary outcomes were the severity and duration of postoperative nausea and vomiting. Secondary outcomes were adverse reactions, use of rescue anti-emetics and patient satisfaction with treatment. Data collection and analysis: Two review authors assessed risk of bias in the included studies and extracted data. As all outcomes analysed were dichotomous, we used a fixed-effects model and calculated relative risk (RR) with associated 95% confidence interval (95% CI). Results: The nine included studies comprised six RCTs and three CCTs with a total of 402 participants. The mean age and range data for all participants were not reported for all studies. The method of randomization in four of the six included RCTs was explicitly stated and adequate. Incomplete reporting of data affected the completeness of the analysis. Compared with placebo, isopropyl alcohol vapour inhalation was effective in reducing the proportion of participants requiring rescue anti-emetics (RR 0.30, 95%CI 0.09 to 1.00, P = 0.05). However, compared with standard anti-emetic treatment, isopropyl alcohol was not effective in reducing the proportion of participants requiring rescue anti-emetics (RR 0.66 95%CI 0.39 to 1.13, P = 0.13) except when the data from a possibly confounded study were included (RR 0.66, 95% CI 0.45 to 0.98, P = 0.04). Where studies reported data on patient satisfaction with aromatherapy, there were no statistically significant differences between the groups (RR 1.12, 95%CI 0.62 to 2.03, P = 0.71). Authors' conclusions: Isopropyl alcohol was more effective than saline placebo for reducing postoperative nausea and vomiting but less effective than standard anti-emetic drugs. There is currently no reliable evidence for the use of peppermint oil.

Reputation modelling in citizen science for environmental acoustic data analysis

Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, as the gathered information is from the crowd, the data quality is always hard to manage. There are many ways to manage data quality, and reputation management is one of the common approaches. In recent year, many research teams have deployed many audio or image sensors in natural environment in order to monitor the status of animals or plants. The collected data will be analysed by ecologists. However, as the amount of collected data is exceedingly huge and the number of ecologists is very limited, it is impossible for scientists to manually analyse all these data. The functions of existing automated tools to process the data are still very limited and the results are still not very accurate. Therefore, researchers have turned to recruiting general citizens who are interested in helping scientific research to do the pre-processing tasks such as species tagging. Although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Therefore, this research aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we aim to investigate how to use reputation management to enhance data reliability. Reputation systems have been used to solve the uncertainty and improve data quality in many marketing and E-Commerce domains. The commercial organizations which have chosen to embrace the reputation management and implement the technology have gained many benefits. Data quality issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. However, research on reputation management in this area is relatively new. We therefore start our investigation by examining existing reputation systems in different domains. Then we design novel reputation management approaches for Citizen Science projects to categorise participants and data. We have investigated some critical elements which may influence data reliability in Citizen Science projects. These elements include personal information such as location and education and performance information such as the ability to recognise certain bird calls. The designed reputation framework is evaluated by a series of experiments involving many participants for collecting and interpreting data, in particular, environmental acoustic data. Our research in exploring the advantages of reputation management in Citizen Science (or crowdsourcing in general) will help increase awareness among organizations that are unacquainted with its potential benefits.

Health complaint commissions in Australia : time for a national approach to data collection

Health complaint statistics are important for identifying problems and bringing about improvements to health care provided by health service providers and to the wider health care system. This paper overviews complaints handling by the eight Australian state and territory health complaint entities, based on an analysis of data from their annual reports. The analysis shows considerable variation between jurisdictions in the ways complaint data are defined, collected and recorded. Complaints from the public are an important accountability mechanism and open a window on service quality. The lack of a national approach leads to fragmentation of complaint data and a lost opportunity to use national data to assist policy development and identify the main areas causing consumers to complain. We need a national approach to complaints data collection in order to better respond to patients’ concerns.

International differences in management of physical activity data: Can they explain some of the difference in prevalence estimates?

Background: National physical activity data suggest that there is a considerable difference in physical activity levels of US and Australian adults. Although different surveys (Active Australia and BRFSS) are used, the questions are similar. Different protocols, however, are used to estimate “activity” from the data collected. The primary aim of this study was to assess whether the 2 approaches to the management of PA data could explain some of the difference in prevalence estimates derived from the two national surveys. Methods: Secondary data analysis of the most recent AA survey (N = 2987). Results: 15% of the sample was defined as “active” using Australian criteria but as “inactive” using the BRFSS protocol, even though weekly energy expenditure was commensurate with meeting current guidelines. Younger respondents (age < 45 y) were more likely to be “misclassified” using the BRFSS criteria. Conclusions: The prevalence of activity in Australia and the US appears to be more similar than we had previously thought.