Applying a multi-agent classifier system with a novel trust measurement method to classifying medical data

In this paper, we present the application of a Multi-Agent Classifier System (MACS) to medical data classification tasks. The MACS model comprises a number of Fuzzy Min-Max (FMM) neural network classifiers as its agents. A trust measurement method is used to integrate the predictions from multiple agents, in order to improve the overall performance of the MACS model. An auction procedure based on the sealed bid is adopted for the MACS model in determining the winning agent. The effectiveness of the MACS model is evaluated using the Wisconsin Breast Cancer (WBC) benchmark problem and a real-world heart disease diagnosis problem. The results demonstrate that stable results are produced by the MACS model in undertaking medical data classification tasks. © 2014 Springer Science+Business Media Singapore.

A hybrid FAM–CART model and its application to medical data classification

In this paper, a hybrid model consisting of the fuzzy ARTMAP (FAM) neural network and the classification and regression tree (CART) is formulated. FAM is useful for tackling the stability–plasticity dilemma pertaining to data-based learning systems, while CART is useful for depicting its learned knowledge explicitly in a tree structure. By combining the benefits of both models, FAM–CART is capable of learning data samples stably and, at the same time, explaining its predictions with a set of decision rules. In other words, FAM–CART possesses two important properties of an intelligent system, i.e., learning in a stable manner (by overcoming the stability–plasticity dilemma) and extracting useful explanatory rules (by overcoming the opaqueness issue). To evaluate the usefulness of FAM–CART, six benchmark medical data sets from the UCI repository of machine learning and a real-world medical data classification problem are used for evaluation. For performance comparison, a number of performance metrics which include accuracy, specificity, sensitivity, and the area under the receiver operation characteristic curve are computed. The results are quantified with statistical indicators and compared with those reported in the literature. The outcomes positively indicate that FAM–CART is effective for undertaking data classification tasks. In addition to producing good results, it provides justifications of the predictions in the form of a decision tree so that domain users can easily understand the predictions, therefore making it a useful decision support tool.

Aggregating privatized medical data for secure querying applications

 This thesis analyses and examines the challenges of aggregation of sensitive data and data querying on aggregated data at cloud server. This thesis also delineates applications of aggregation of sensitive medical data in several application scenarios, and tests privatization techniques to assist in improving the strength of privacy and utility.

Medical data classification using interval type-2 fuzzy logic system and wavelets

This paper introduces an automated medical data classification method using wavelet transformation (WT) and interval type-2 fuzzy logic system (IT2FLS). Wavelet coefficients, which serve as inputs to the IT2FLS, are a compact form of original data but they exhibits highly discriminative features. The integration between WT and IT2FLS aims to cope with both high-dimensional data challenge and uncertainty. IT2FLS utilizes a hybrid learning process comprising unsupervised structure learning by the fuzzy c-means (FCM) clustering and supervised parameter tuning by genetic algorithm. This learning process is computationally expensive, especially when employed with high-dimensional data. The application of WT therefore reduces computational burden and enhances performance of IT2FLS. Experiments are implemented with two frequently used medical datasets from the UCI Repository for machine learning: the Wisconsin breast cancer and Cleveland heart disease. A number of important metrics are computed to measure the performance of the classification. They consist of accuracy, sensitivity, specificity and area under the receiver operating characteristic curve. Results demonstrate a significant dominance of the wavelet-IT2FLS approach compared to other machine learning methods including probabilistic neural network, support vector machine, fuzzy ARTMAP, and adaptive neuro-fuzzy inference system. The proposed approach is thus useful as a decision support system for clinicians and practitioners in the medical practice. copy; 2015 Elsevier B.V. All rights reserved.

The initiation and administration of drugs for advanced life support by critical care nurses in the absence of a medical practitioner

Current legislation does not permit the administration of first line resuscitation medications by suitably qualified Division 1 registered nurses (RNs) in the absence of a medical officer. This omission by the Drugs,  Poisons and Controlled Substances Act 1981 (Vic) and the Drugs, Poisons and The Controlled Substances Regulations 1995 (Vic) leaves many critical care nurses in a vulnerable legal position.

The primary aim of this study was to gauge the view of critical care nurses with respect to lobbying for change to the current legislation. In addition, the study aimed to explore and describe the educational preparation, practice perceptions and experiences of RNs working in critical care regarding cardiopulmonary resuscitation and the administration of first line advanced life support (ALS) medications in the absence of a medical officer. It was anticipated that data collected would demonstrate some of the dilemmas associated with the initiation and administration of ALS medications for practising critical care nurses and could be used to inform controlling bodies in order for them to gain an appreciation of the issues facing critical care nurses during resuscitation.

A mailout survey was sent to all members of the Victorian Branch of the Australian College of Critical Care Nurses (ACCCN). The results showed that the majority of nurses underwent an annual ALS assessment and had current ALS accreditation. Nurses indicated that they felt educationally prepared and were confident to manage cardiopulmonary resuscitation without a medical officer; indeed, the majority had done so. The differences in practice issues for metropolitan, regional and rural nurses were highlighted. There is therefore clear evidence to suggest that legislative amendments are appropriate and necessary, given the time critical nature of cardiopulmonary arrest. There was overwhelming support for ACCCN Vic. Ltd to lobby the Victorian government for changes to the law.

Microarray data classification using automatic SVM kernel selection

Microarray data classification is one of the most important emerging clinical applications in the medical community. Machine learning algorithms are most frequently used to complete this task. We selected one of the state-of-the-art kernel-based algorithms, the support vector machine (SVM), to classify microarray data. As a large number of kernels are available, a significant research question is what is the best kernel for patient diagnosis based on microarray data classification using SVM? We first suggest three solutions based on data visualization and quantitative measures. Different types of microarray problems then test the proposed solutions. Finally, we found that the rule-based approach is most useful for automatic kernel selection for SVM to classify microarray data.

The need for best practice standards in electronic governance of patient medical records to facilitate innovation

Background : Optimising the use of electronic data offers many opportunities to health services, particularly in rural and remote areas. These include reducing the effect of distance on access to clinical information and sharing information where there are multiple service providers for a single patient. The increasing compilation of large electronic databases of patient information and the ease with which electronic information can be transferred has raised concerns about the privacy and confidentiality of such records.
Aims & rationale/Objectives : This review aims to identify legal and ethical standards for areas of electronic governance where a lack of clarity may currently impede innovation in health service delivery.
Methods : This paper describes best practices for storage and transfer of electronic patient data based on an examination of Australian legislative requirements and a review of a number of current models. This will firstly allow us to identify basic legal requirements of electronic governance as well as areas of ambiguity not fully addressed by legislation. An examination of current models will suggest recommendations for best practice in areas lacking sufficient legal guidance.
Principal findings : We have identified the following four areas of importance, and shall discuss relevant details:
1) Patients' right of ownership to electronic patient records. 2) Custodial issues with data stored in centralised health care institutions 3) IT Security, including hierarchical level access, data encryption, data transfer standards and physical security 4) Software applications usage.
Discussion : Our examination of several models of best practice for the transfer of electronic patient data, both in Australia and internationally, identifies and clarifies many unresolved issues of electronic governance. This paper will also inform future policy in this area.
Implications : Clarification will facilitate the future development of beneficial technology-based innovations by rural health services.
Presentation type : Poster

Medical knowledge discovery from a regional asthma dataset

Paediatric asthma represents a significant public health problem. To date, clinical data sets have typically been examined using traditional data analysis techniques. While such traditional statistical methods are invariably widespread, large volumes of data may overwhelm such approaches. The new generation of knowledge discovery techniques may therefore be a more appropriate means of analysis. The primary purpose of this study was to investigate an asthma data set, with the application of various data mining techniques for knowledge discovery. The current study utilises data from an asthma data set (n ≈ 17000). The findings revealed a number of factors and patterns of interest.

Enhancing the health of medical students : outcomes of an integrated mindfulness and lifestyle program

Medical students experience various stresses and many poor health behaviours. Previous studies consistently show that student wellbeing is at its lowest pre-exam. Little core-curriculum is traditionally dedicated to providing self-care skills for medical students. This paper describes the development, implementation and outcomes of the Health Enhancement Program (HEP) at Monash University. It comprises mindfulness and ESSENCE lifestyle programs, is experientially-based, and integrates with biomedical sciences, clinical skills and assessment. This study measured the program’s impact on medical student psychological distress and quality of life. A cohort study performed on the 2006 first-year intake measured effects of the HEP on various markers of wellbeing. Instruments used were the depression, anxiety and hostility subscales of the Symptom Checklist-90-R incorporating the Global Severity Index (GSI) and the WHO Quality of Life (WHOQOL) questionnaire. Pre-course data (T1) was gathered mid-semester and post-course data (T2) corresponded with pre-exam week. To examine differences between T1 and T2 repeated measures ANOVA was used for the GSI and two separate repeated measures MANOVAs were used to examine changes in the subscales of the SCL-90-R and the WHOQOL-BREF. Follow-up t-tests were conducted to examine differences between individual subscales. A total of 148 of an eligible 270 students returned data at T1 and T2 giving a response rate of 55%. 90.5% of students reported personally applying the mindfulness practices. Improved student wellbeing was noted on all measures and reached statistical significance for the depression (mean T1 = 0.91, T2 = 0.78; p = 0.01) and hostility (0.62, 0.49; 0.03) subscales and the GSI (0.73, 0.64; 0.02) of the SCL-90, but not the anxiety subscale (0.62, 0.54; 0.11). Statistically significant results were also found for the psychological domain (62.42, 65.62; p < 0.001) but not the physical domain (69.11, 70.90; p = 0.07) of the WHOQOL. This study is the first to demonstrate an overall improvement in medical student wellbeing during the pre-exam period suggesting that the common decline in wellbeing is avoidable. Although the findings of this study indicate the potential for improving student wellbeing at the same time as meeting important learning objectives, the limitations in study design due to the current duration of follow-up and lack of a control group means that the data should be interpreted with caution. Future research should be directed at determining the contribution of individual program components, long-term outcomes, and impacts on future attitudes and clinical practice.

Determining clinical pharmacy workload by patient disease classification in medical and surgical patients

Aim: To determine the time needed to provide clinical pharmacy services to individual patient episodes for medical and surgical patients and the effect of patient presentation and complexity on the clinical pharmacy workload. Method: During a 5-month period in 2006 at two general hospitals, pharmacists recorded a defined range of activities that they provided for patients, including the actual times required for these tasks. A customised database linked to the two hospitals' patient administration systems stored the data according to the specific patient episode number. The influence of patient presentation and complexity on the clinical pharmacy activities provided was also examined. Results: The average time required by pharmacists to undertake a medication history interview and medication reconciliation was 9.6 (SD 4.9) minutes. Interventions required 5.7 (SD 4.6) minutes, clinical review of the medical record 5.5 (SD 4.0) minutes and medication order review 3.5 (SD 2.0) minutes. For all of these activities, the time required for medical patients was greater than for surgical patients and greater for 'complicated' patients. The average time required to perform all clinical pharmacy activities for 1071 completed patient episodes was 14.4 (SD 10.9) minutes and was greater for medical and 'complicated' patients. Conclusion: The time needed to provide clinical pharmacy services was affected by whether the patients were medical or surgical. The existence of comorbidities or complications affected these times. The times required to perform clinical pharmacy activities may not be consistent with recently proposed staff ratios for the provision of a basic clinical pharmacy service.

Why do medical graduates choose rural careers?

Introduction: This study is based on the metaphor of the ‘rural pipeline’ into medical practice. The four stages of the rural
pipeline are: (1) contact between rural secondary schools and the medical profession; (2) selection of rural students into medical
programs; (3) rural exposure during medical training; and (4) measures to address retention of the rural medical workforce.
Methods: Using the rural pipeline template we conducted a literature review, analysed the selection methods of Australian
graduate entry medical schools and interviewed 17 interns about their medical career aspirations.
Results: Literature review: The literature was reviewed to assess the effectiveness of selection practices to predict successful
gradation and the impact of rural pipeline components on eventual rural practice. Undergraduate academic performance is the
strongest predictor of medical course academic performance. The predictive power of interviews is modest. There are limited data
on the predictive power of other measures of non-cognitive performance or the content of the undergraduate degree. Prior rural
residence is the strongest predictor of choice of a rural career but extended rural exposure during medical training also has a
significant impact. The most significant influencing factors are: professional support at national, state and local levels; career
pathway opportunities; contentedness of the practitioner’s spouse in rural communities; preparedness to adopt a rural lifestyle;
educational opportunities for children; and proximity to extended family and social circle. Analysis of selection methods: Staff
involved in student selection into 9 Australian graduate entry medical schools were interviewed. Four themes were identified:
(1) rurality as a factor in student selection; (2) rurality as a factor in student selection interviews; (3) rural representation on student
selection interview panels; (4) rural experience during the medical course. Interns’ career intentions: Three themes were identified:
(1) the efficacy of the rural pipeline; (2) community connectedness through the rural pipeline; (3) impediments to the effect of the
rural pipeline, the most significant being a partner who was not committed to rural life
Conclusion: Based on the literature review and interviews, 11 strategies are suggested to increase the number of graduates
choosing a career in rural medicine, and one strategy for maintaining practitioners in rural health settings after graduation.

Oxygen delivery to patients after cardiac surgery : a medical record audit

OBJECTIVE: To describe how intensive care nurses manage the administration of supplemental oxygen to patients during the first 24 hours after cardiac surgery.
METHODS: A retrospective audit was conducted of the medical records of 245 adult patients who underwent cardiac surgery between 1 January 2005 and 31 May 2008 in an Australian metropolitan hospital. Physiological data (oxygen saturation measured by pulse oximetry and respiratory rate) and intensive care unit management data (oxygen delivery device, oxygen flow rate and duration of mechanical ventilation) were collected at hourly intervals over the first 24 hours of ICU care.
RESULTS: Of the 245 patients whose records were audited, 185 were male; mean age was 70 years (SD, 10), and mean APACHE II score was 17.5 (SD, 5.14). Almost half the patients (122, 49.8%) were extubated within 8 hours of ICU admission. The most common oxygen delivery device used immediately after extubation was the simple face mask (214 patients, 87%). Following extubation, patients received supplemental oxygen via, on average, two different delivery devices (range, 1-3), and had the delivery device changed an average of 1.38 times (range, 0-6) during the 24 hours studied. Twenty-two patients (9%) received non-invasive ventilation or high-flow oxygen therapy, and 16 (7%) experienced one or more episode of hypoxaemia during mechanical ventilation. A total of 148 patients (60%) experienced one or more episodes of low oxygenation or abnormal respiratory rate during the first 24 hours of ICU care despite receiving supplemental oxygen.
CONCLUSION: These findings suggest that the ICU environment does not protect cardiac surgical patients from suboptimal oxygen delivery, and highlights the need for strategies to prompt the early initiation of interventions aimed at optimising blood oxygen levels in cardiac surgical patients in the ICU.

Medical error and decision making : learning from the past and present in intensive care

Background : Human error occurs in every occupation. Medical errors may result in a near miss or an actual injury to a patient that has nothing to do with the underlying medical condition. Intensive care has one of the highest incidences of medical error and patient injury in any specialty medical area; thought to be related to the rapidly changing patient status and complex diagnoses and treatments.

Purpose : The aims of this paper are to: (1) outline the definition, classifications and aetiology of medical error; (2) summarise key findings from the literature with a specific focus on errors arising from intensive care areas; and (3) conclude with an outline of approaches for analysing clinical information to determine adverse events and inform practice change in intensive care.

Data source : Database searches of articles and textbooks using keywords: medical error, patient safety, decision making and intensive care. Sociology and psychology literature cited therein.

Findings : Critically ill patients require numerous medications, multiple infusions and procedures. Although medical errors are often detected by clinicians at the bedside, organisational processes and systems may contribute to the problem. A systems approach is thought to provide greater insight into the contributory factors and potential solutions to avoid preventable adverse events.

Conclusion : It is recommended that a variety of clinical information and research techniques are used as a priority to prevent hospital acquired injuries and address patient safety concerns in intensive care.