Progressive Horizon Planning - Planning Exploratory-Corrective Behavior

Much planning research assumes that the goals for which one plans are known in advance. That is not true of trauma management, which involves both a search for relevant goals and reasoning about how to achieve them. TraumAID is a consultation system for the diagnosis and treatment of multiple trauma. It has been under development jointly at the University of Pennsylvania and the Medical College of Pennsylvania for the past eight years. TraumAID integrates diagnostic reasoning, planning and action. Its reasoner identifies diagnostic and therapeutic goals appropriate to the physician’s knowledge of the patient’s state, while its planner advises on beneficial actions to next perform. The physician’s lack of complete knowledge of the situation and the time limitations of emergency medicine constrain the ability of any planner to identify what would be the best thing to do. Nevertheless, TraumAID’s Progressive Horizon Planner has been designed to create a plan for patient care that is in keeping with the standards of managing trauma

Towards Goal-Directed Diagnosis (Preliminary Report)

Recent research has abstracted diagnosis away from the activity needed to acquire information and to act on diagnosed disorders. In some problem domains, however, such abstraction is counter-productive and does not reflect real-life practice, which integratesdiagnostic and therapeutic activity. Trauma management is a case in point. Here, we discuss a formalization of the integrated approach taken in TraumAID, a system we have developed to serve as an artificial aide to residents and physicians dealing with multiple trauma. Among other things, the active pursuit of information raises the question of what is and what is not worth pursuing. In TraumAID 2.0, we take the view that the process of diagnosis should continue only as long as it is likely to make a difference to future actions. That view is formalized in the goal-directed diagnostic paradigm (GDD). Unlike other diagnostic paradigms, goal-directed diagnosis is first and foremost concerned with setting goals based on its conclusions. It regards the traditional construction of an explanation for the faulty behavior as secondary. In order to explicitly represent goal-directedness, the diagnostic process is viewed as search in a space of attitude-beliefs. From this, we derive a high-level algorithm that produces appropriate requests for action while searching for an explanation. A complete explanation, however, is not the criterion for terminating action. Such a criterion, we argue, is better treated in terms of goal-means tradeoffs. TraumAID\u27s architecture, in so far as it embodies this goal-directed approach, assigns to a complementary planner the resolution of such tradeoffs

Flexible Support for Trauma Management Through Goal-Directed Reasoning and Planning

We describe a system, TraumAID, which has been designed to provide decision support throughout the initial definitive management of severely injured patients (i.e., after their initial evaluation, resuscitation, and stabilization). Over the course of initial definitive management, TraumAID recommends appropriate procedures to be carried out, based on currently available evidence and on the complexity and urgency of the situation. TraumAID\u27s ability to deal flexibly with complex and often urgent situations comes from its ability to reason separately about the management goals that should be achieved and about the means that are situationally appropriate for achieving them. In this paper, we describe TraumAID\u27s approach to trauma management in more detail, showing in particular how it enables TraumAID to adapt its reasoning and recommendations to the urgency with which a patient\u27s condition must be addressed

Progressive Horizon Planning

In an earlier paper [Rymon et a1 89], we showed how domain localities and regularities can be used to reduce the complexity of finding a trauma management plan that satisfies a set of diagnostic and therapeutic goals. Here, we present another planning idea - Progressive Horizon - useful for optimizing such plans in domains where planning can be regarded as an incremental process, continuously interleaved with situation - goals analysis and plan execution. In such domains, planned action cannot be delayed until all essential information is available: A plan must include actions intended to gather information as well as ones intended to change the state of the world. Interleaving planning with reasoning and execution, a progressive horizon planner constructs a plan that answers all currently known needs but has only its first few actions optimized (those within its planning horizon). As the executor cames out actions and reports back to the system, the current goals and the plan are updated based on actual performance and newly discovered goals and information. The new plan is then optimized within a newly set horizon. In this paper, we describe those features of a domain that are salient for the use of a progressive horizon planning paradigm. Since we believe that the paradigm may be useful in other domains, we abstract from the exact techniques used by our program to discuss the merits of the general approach

TraumAID: AI Support in the Management of Multiple Trauma

This paper outlines the particular demands that multiple trauma makes on systems designed to provide appropriate decision support, and the ways that these demands are currently being met in our system, TraumAID. The demands follow from: (1) the nature of trauma and the procedures used in its diagnosis, (2) the need to adjust diagnostic and therapeutic procedures to available resource levels, (3) the role of anatomy in trauma and the need for anatomical reasoning, (4) the role of non-specialists in managing trauma, and (5) the competing demands of multiple injuries and the consequent need for planning. We believe that these demands are not unique to multiple trauma, so that the paper may be of general interest to expert system research and development

TraumAID: Reasoning and Planning in the Initial Definitive Management of Multiple Injuries

The TraumAID system has been designed to provide computerized decision support to optimize the initial definitive management of acutely injured patients after resuscitation and stabilization. The currently deployed system, TraumAID 1.0, addresses penetrating injuries to the abdomen and to the chest. Our experience with TraumAID 1.0 has demonstrated some major deficiencies in rule-based reasoners that are faced with problems of both diagnosis and treatment. To address these deficiencies, we have redesigned the system (TraumAID 2.0), factoring it into two modules: (1) a rule-based reasoner embodying the knowledge and logical machinery needed to link clinical evidence to diagnostic and therapeutic goals, and (2) a planner embodying the global knowledge and logical machinery needed to create a plan that addresses combinations of goals. After describing TraumAID 2.0, we discuss an extension of the TraumAID interface (critique mode interaction) that may improve its acceptability in a clinical setting. We close with a brief discussion of management support in resource-limited environments, which is an important issue in the time-critical context of multiple trauma

The gut microbiota: a major player in the toxicity of environmental pollutants?

Exposure to environmental chemicals has been linked to various health disorders, including obesity, type 2 diabetes, cancer and dysregulation of the immune and reproductive systems, whereas the gastrointestinal microbiota critically contributes to a variety of host metabolic and immune functions. We aimed to evaluate the bidirectional relationship between gut bacteria and environmental pollutants and to assess the toxicological relevance of the bacteria–xenobiotic interplay for the host. We examined studies using isolated bacteria, faecal or caecal suspensions—germ-free or antibiotic-treated animals—as well as animals reassociated with a microbiota exposed to environmental chemicals. The literature indicates that gut microbes have an extensive capacity to metabolise environmental chemicals that can be classified in five core enzymatic families (azoreductases, nitroreductases, β-glucuronidases, sulfatases and β-lyases) unequivocally involved in the metabolism of >30 environmental contaminants. There is clear evidence that bacteria-dependent metabolism of pollutants modulates the toxicity for the host. Conversely, environmental contaminants from various chemical families have been shown to alter the composition and/or the metabolic activity of the gastrointestinal bacteria, which may be an important factor contributing to shape an individual’s microbiotype. The physiological consequences of these alterations have not been studied in details but pollutant-induced alterations of the gut bacteria are likely to contribute to their toxicity. In conclusion, there is a body of evidence suggesting that gut microbiota are a major, yet underestimated element that must be considered to fully evaluate the toxicity of environmental contaminants