Reasoning paradigms in legal decision support systems

In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approaches used in legal domains. Symbolic reasoning systems which rely on deductive, inductive and analogical reasoning are described and reviewed. The role of statistical reasoning in law is examined, and the use of neural networks analysed. There is discussion of architectures for, and examples of, systems which combine a number of these reasoning strategies. We conclude that to build intelligent legal decision support systems requires a range of reasoning strategies.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

"The red dress or the blue?" How do staff perceive that they support decision making for people with dementia living in residential aged care facilities?

Respect for a person's right to make choices and participate in decision making is generally seen as central to quality of life and well-being. When a person moves into a residential aged care facility (RACF), however, decision making becomes more complicated, particularly if the person has a diagnosis of dementia. Little is known about how staff in RACFs perceive that they support decision making for people with dementia within their everyday practice, and this article seeks to address this knowledge gap. The article reports on the findings of a qualitative study conducted in the states of Victoria and Queensland, Australia with 80 direct care staff members. Findings revealed that the participants utilized a number of strategies in their intention to support decision making for people with dementia, and had an overall perception that "a little effort goes a long way."

Robust conservation decision-making

Decision-making for conservation is conducted within the margins of limited funding. Furthermore, to allocate these scarce resources we make assumptions about the relationship between management impact and expenditure. The structure of these relationships, however, is rarely known with certainty. We present a summary of work investigating the impact of model uncertainty on robust decision-making in conservation and how this is affected by available conservation funding. We show that achieving robustness in conservation decisions can require a triage approach, and emphasize the need for managers to consider triage not as surrendering but as rational decision making to ensure species persistence in light of the urgency of the conservation problems, uncertainty, and the poor state of conservation funding. We illustrate this theory by a specific application to allocation of funding to reduce poaching impact on the Sumatran tiger Panthera tigris sumatrae in Kerinci Seblat National Park, Indonesia. To conserve our environment, conservation managers must make decisions in the face of substantial uncertainty. Further, they must deal with the fact that limitations in budgets and temporal constraints have led to a lack of knowledge on the systems we are trying to preserve and on the benefits of the actions we have available (Balmford & Cowling 2006). Given this paucity of decision-informing data there is a considerable need to assess the impact of uncertainty on the benefit of management options (Regan et al. 2005). Although models of management impact can improve decision making (e.g.Tenhumberg et al. 2004), they typically rely on assumptions around which there is substantial uncertainty. Ignoring this 'model uncertainty', can lead to inferior decision-making (Regan et al. 2005), and potentially, the loss of the species we are trying to protect. Current methods used in ecology allow model uncertainty to be incorporated into the model selection process (Burnham & Anderson 2002; Link & Barker 2006), but do not enable decision-makers to assess how this uncertainty would change a decision. This is the basis of information-gap decision theory (info-gap); finding strategies most robust to model uncertainty (Ben-Haim 2006). Info-gap has permitted conservation biology to make the leap from recognizing uncertainty to explicitly incorporating severe uncertainty into decision-making. In this paper we present a summary of McDonald-Madden et al (2008a) who use an info-gap framework to address the impact of uncertainty in the functional representations of biological systems on conservation decision-making. Furthermore, we highlight the importance of two key elements limiting conservation decision-making - funding and knowledge - and how they interact to influence the best management strategy for a threatened species. Copyright © ASCE 2011.

Optimizing preventative maintenance strategies for linear assets

Linear assets are engineering infrastructure, such as pipelines, railway lines, and electricity cables, which span long distances and can be divided into different segments. Optimal management of such assets is critical for asset owners as they normally involve significant capital investment. Currently, Time Based Preventive Maintenance (TBPM) strategies are commonly used in industry to improve the reliability of such assets, as they are easy to implement compared with reliability or risk-based preventive maintenance strategies. Linear assets are normally of large scale and thus their preventive maintenance is costly. Their owners and maintainers are always seeking to optimize their TBPM outcomes in terms of minimizing total expected costs over a long term involving multiple maintenance cycles. These costs include repair costs, preventive maintenance costs, and production losses. A TBPM strategy defines when Preventive Maintenance (PM) starts, how frequently the PM is conducted and which segments of a linear asset are operated on in each PM action. A number of factors such as required minimal mission time, customer satisfaction, human resources, and acceptable risk levels need to be considered when planning such a strategy. However, in current practice, TBPM decisions are often made based on decision makers’ expertise or industrial historical practice, and lack a systematic analysis of the effects of these factors. To address this issue, here we investigate the characteristics of TBPM of linear assets, and develop an effective multiple criteria decision making approach for determining an optimal TBPM strategy. We develop a recursive optimization equation which makes it possible to evaluate the effect of different maintenance options for linear assets, such as the best partitioning of the asset into segments and the maintenance cost per segment.

A decision-analysis-based framework for analysing stakeholder behaviour in scenario planning

Scenario planning is a method widely used by strategic planners to address uncertainty about the future. However, current methods either fail to address the future behaviour and impact of stakeholders or they treat the role of stakeholders informally. We present a practical decision-analysis-based methodology for analysing stakeholder objectives and likely behaviour within contested unfolding futures. We address issues of power, interest, and commitment to achieve desired outcomes across a broad stakeholder constituency. Drawing on frameworks for corporate social responsibility (CSR), we provide an illustrative example of our approach to analyse a complex contested issue that crosses geographic, organisational and cultural boundaries. Whilst strategies can be developed by individual organisations that consider the interests of others – for example in consideration of an organisation's CSR agenda – we show that our augmentation of scenario method provides a further, nuanced, analysis of the power and objectives of all concerned stakeholders across a variety of unfolding futures. The resulting modelling framework is intended to yield insights and hence more informed decision making by individual stakeholders or regulators.

Transforming beyond self: fluidity of parent identity in family decision-making

When a household welcomes a new infant a transformation occurs whereby household routines, values and decisions change. This research explores how decision-making is influenced by fluctuating identity subjectivities. We explore longitudinally, using a family identity framework, how the transitioning between self, couple and family self-identities influences the decisions made regarding social issues, in this case infant feeding. Results indicate that decision-making during a period of transformation is not straightforward, relying on a multiplicity of identities that are constantly renegotiated and dependent on other influences. Decisions made conform to the identity-construct-of-the-moment, but are fluid and subject to change, such that pinpointing causal pathways is inappropriate. Implications for influencing the consumption of social behaviors for consumer researchers are one size does not fit all and require an in-depth understanding of the fluidity of decision-making. Consequently, social marketing strategies need to be tailored to constructed identities and flexible across time to remain influential.

Decision-theoretic designs for dose-finding clinical trials with multiple outcomes

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

Patient decision aids in routine maternity care: Benefits, barriers, and new opportunities

Background and aim Participation in decision-making, supported by comprehensive and quality information provision, is increasingly emphasised as a priority for women in maternity care. Patient decision aids are tools that can offer women greater access to information and guidance to participate in maternity care decision-making. Relative to their evaluation in controlled settings, the implementation of patient decision aids in routine maternity care has received little attention and our understanding of which approaches may be effective is limited. This paper critically discusses the application of patient decision aids in routine maternity care and explores viable solutions for promoting their successful uptake. Discussion A range of patient decision aids have been developed for use within maternity care, and controlled trials have highlighted their positive impact on the decision-making process for women. Nevertheless, evidence of successful patient decision aid implementation in real world health care settings is lacking due to practical and ideological barriers that exist. Patient-directed social marketing campaigns are a relatively novel approach to patient decision aid delivery that may facilitate their adoption in maternity care, at least in the short-term, by overcoming common implementation barriers. Social marketing may also be particularly well suited to maternity care, given the unique characteristics of this health context. Conclusions The potential of social marketing campaigns to facilitate patient decision aid adoption in maternity care highlights the need for pragmatic trials to evaluate their effectiveness. Identifying which sub-groups of women are more or less likely to respond to these strategies will further direct implementation.

Doctors’ perspectives on law and life-sustaining treatment: Survey design and recruitment strategies for a challenging cohort

- Background Palliative medicine and other specialists play significant legal roles in decisions to withhold and withdraw life-sustaining treatment at the end of life. Yet little is known about their knowledge of or attitudes to the law, and the role they think it should play in medical practice. Consideration of doctors’ views is critical to optimizing patient outcomes at the end of life. However, doctors are difficult to engage as participants in empirical research, presenting challenges for researchers seeking to understand doctors’ experiences and perspectives. - Aims To determine how to engage doctors involved in end-of-life care in empirical research about knowledge of the law and the role it plays in medical practice at the end of life. - Methods Postal survey of all specialists in palliative medicine, emergency medicine, geriatric medicine, intensive care, medical oncology, renal medicine, and respiratory medicine in three Australian states: New South Wales, Victoria, and Queensland. The survey was sent in hard copy with two reminders and a follow up reminder letter was also sent to the directors of hospital emergency departments. Awareness was further promoted through engagement with the relevant medical colleges and publications in professional journals; various incentives to respond were also used. The key measure is the response rate of doctors to the survey. - Results Thirty-two percent of doctors in the main study completed their survey with response rate by specialty ranging from 52% (palliative care) to 24% (medical oncology). This overall response rate was twice that of the reweighted pilot study (16%). - Conclusions Doctors remain a difficult cohort to engage in survey research but strategic recruitment efforts can be effective in increasing response rate. Collaboration with doctors and their professional bodies in both the development of the survey instrument and recruitment of participants is essential.