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At least 307 records · Page 17Linked to original sources
PubMed2002

A methodology for missile countermeasures optimization under uncertainty.

The missile countermeasures optimization problem is a complex strategy optimization problem that combines aircraft maneuvers with additional countermeasures in an attempt to survive attack from a single surface-launched, anti-aircraft missile. Classic solutions require the evading aircraft to execute specific sequences of maneuvers at precise distances from the pursuing missile and do not effectively account for uncertainty about the type and/or current state of the missile. This paper defines a new methodology for solving the missile countermeasures optimization problem under conditions of uncertainty. The resulting genetic programming system evolves programs that combine maneuvers with such countermeasures as chaff, flares, and jamming to optimize aircraft survivability. This methodology may be generalized to solve strategy optimization problems for intelligent, autonomous agents operating under conditions of uncertainty.

Aircraft↗
PubMed2003

An advanced artificial intelligence tool for menu design.

The computer-assisted menu design still remains a difficult task. Usually knowledge that aids in menu design by a computer is hard-coded and because of that a computerised menu planner cannot handle the menu design problem for an unanticipated client. To address this problem we developed a menu design tool, MIKAS (menu construction using incremental knowledge acquisition system), an artificial intelligence system that allows the incremental development of a knowledge-base for menu design. We allow an incremental knowledge acquisition process in which the expert is only required to provide hints to the system in the context of actual problem instances during menu design using menus stored in a so-called Case Base. Our system incorporates Case-Based Reasoning (CBR), an Artificial Intelligence (AI) technique developed to mimic human problem solving behaviour. Ripple Down Rules (RDR) are a proven technique for the acquisition of classification knowledge from expert directly while they are using the system, which complement CBR in a very fruitful way. This combination allows the incremental improvement of the menu design system while it is already in routine use. We believe MIKAS allows better dietary practice by leveraging a dietitian's skills and expertise. As such MIKAS has the potential to be helpful for any institution where dietary advice is practised.

Artificial Intelligence↗
PubMedDate not supplied

Knowledge acquisition and verification tools for medical expert systems.

Expert systems require large amounts of domain knowledge for non-trivial problem solving. Experience in developing such systems has shown that the processes of acquiring domain knowledge (knowledge acquisition) and of determining whether the knowledge is consistent, complete, and correct (knowledge verification) are major problems. This paper discusses various tools developed to assist in these two processes. These tools bring additional knowledge to bear, or provide better interfaces between a knowledge engineer and the expert system's knowledge.

Artificial Intelligence↗
PubMedDate not supplied

HYDRA: a knowledge acquisition tool for expert systems that critique medical workup.

HYDRA is a computer-based knowledge acquisition tool under development to assist in the creation of expert systems which critique medical workup. To use HYDRA, a domain expert first outlines the recommended approaches to the workup of a chosen medical problem, using the Augmented Transition Network formalism. From this model, HYDRA produces a list of the various conditions for which critiquing comments may be required to react to all possible approaches that might be proposed by the user of the critiquing system. Domain-specific constraints can be used to restrict the number of conditions suggested. In this way, HYDRA assists the domain expert by providing a model for structuring the problem, and by breaking down the domain expert's work into a set of small, easily understood tasks.

Algorithms↗
PubMed2005

Scanning the horizon: emerging hospital-wide technologies and their impact on critical care.

This commentary represents a selective survey of developments relevant to critical care. Selected themes include advances in point-of-care diagnostic testing, glucose control, novel microbiological diagnostics and infection control measures, and developments in information technology that have implications for intensive care. The latter encompasses an early example of an artificially intelligent clinical decision support mechanism, the introduction of a national health care information technology programme (UK NPfIT) and its implications, and exotic threats to patient safety due to emergent behaviour in complex information systems.

Biomedical Technology↗
PubMedDate not supplied

Medical and psychiatric complications of cocaine abuse with possible points of pharmacological treatment.

Acute and chronic medical complications of cocaine abuse are dependent on cocaine's route of administration, purity and sterility. There is a predictable sequence of events which occur during cocaine withdrawal. Cocaine can cause or exacerbate psychiatric symptoms indistinguishable from a classical psychiatric disorder. IV and freebase abuse is more likely to precipitate psychiatric symptoms. Systematic medical and psychiatric evaluation in addition to detoxification allows the detection and treatment of relapse-causing conditions. This permits more intelligent treatment decisions. Possible points of pharmacological intervention are discussed and new treatments proposed.

Administration, Intranasal↗
PubMed2005

Comparison of different methods for hemodialysis evaluation by means of ROC curves: from artificial intelligence to current methods.

BACKGROUND: The National Kidney Foundation Guidelines (DOQI) and the European Renal Association (ERA) have set standards for adequacy of hemodialysis treatment. They recommended minimum single pool doses of 1.2 (Kt/Vsp DOQI), and 1.4 (Kt/Vsp ERA) and a "standard" urea removal ratio (URR) of 65%. Here, we compare an Artificial Intelligence Method (AIM) based on an Artificial Neural Network (ANN) and the usual methods for hemodialysis treatment follow-up such as Smye, Daugirdas, standard urea reduction ratio (URR using post-dialysis urea concentration) and modified URR [Cheng et al. 2001] against equilibrated Kt/V and URR calculated using a 60 min post-dialysis urea concentration. METHODS: We used ROC analysis to evaluate and compare these methodologies. We also propose a method to find a minimum target dose that maximizes the sensitivity, specificity and positive predictive values of the diagnostic tool. RESULTS: From a URR point of view, the ANN, stdURR and mURR perform almost equally well with an area under the curve (AUC) of 0.90, 0.93 and 0.92, respectively, but the ANN achieved the lowest false positive rate (FPR = 7.94%) and error rate (ER = 12.7%). When Kt/V is used as a dose index, the logarithmic single-and double-pool equations perform almost equally (AUC 0.957 and 0.962), and the ANN method achieves an AUC of 0.934. The lowest FPR was for ANN and Kt/Vsp (4.76%), which also achieved the lowest ER of 6.39%. CONCLUSIONS: For both cases (URR and Kt/V), the minimum doses required to achieve the lowest FPR and ER for the standard methods (stdURR and Kt/Vsp) were higher than those reported by the DOQI guidelines, being 70% for stdURR and 1.35 for Kt/Vsp, whereas for those methods using the double-pool Kt/V or equilibrated URR, the dose targets were close to those recommended by DOQI and ERA. Our proposed method for target dose selection is easy to understand, and it takes into account both accuracy and confidence of the adequacy tool. We found the ANN method to be superior to the Smye method for estimation of equilibrated urea, and the results presented here suggest that ANN methods could be useful tools in the analysis of nephrology data.

Artificial Intelligence↗
PubMed1993

Contrasting acute care and long-term care information systems needs.

Information systems in nursing facilities have their own set of requirements. While these may appear to be less complex than those required of acute care systems, they offer their own series of traps and pitfalls and the information systems manager should be wary of vendors who suggest that acute care systems can be readily modified for long-term care usage. Well-designed and implemented long-term care applications demand the same challenges to integration as do acute care products. Information provided by these systems must be designed to support not only the routine transactions of the facility, but also the strategic planning necessary for intelligent management decision making. It is not sufficient in this era to record and replay data. Data must be synthesized into meaningful summaries in order to be effectively used by executives. [7] This is also true for clinicians. Assessment data are increasingly used to position a patient in a case-mix or reimbursement group. Whereas acute care revolves around DRGs and ICD-9 codes (soon to be ICD-10), long-term care uses a patient review instrument (PRI), resident assessment protocols (RAPs), and resource utilization groups (RUGS). The successful information systems manager will have all of these measures at his or her disposal by financial class, insurance class, and days receivable if eyes are kept on the goal of planning all of the systems with equal care and an eye to the future.

Acute Disease↗
PubMed1995

Prescription guidelines in OPADE: what are they, how are they used?

Many computerised drug prescription systems have been developed, but they are rarely used in clinical practice; among the reasons are their lack of integration with the functioning of medical institutions and the lack of consideration of general and local clinical practice rules. We present in this paper how OPADE, a computerised drug prescription system does answer this shortcoming by introducing prescription guidelines called Prescribing Principles. We argue that introduction of these Prescribing Principles will not only allow for integration of the computer in medical practice but will also introduce a positive feed back loop in the prescribing process.

Artificial Intelligence↗
PubMed1995

Framework for quality assessment of knowledge.

One of the key issues in the development (and subsequent application) of medical knowledge-be it in terms of a KBS or otherwise-is the assessment of its quality. We present a framework for how to manage and make measurable the quality of the semantic as well as pragmatic aspects of the knowledge embedded in classification models during the development of such models.

Artificial Intelligence↗
PubMed1989

Preparing women for the profession: a course using structured role-model analysis.

In response to increasing numbers of women entering pharmacy, a course was developed at the University of California, San Francisco, School of Pharmacy, addressing issues facing women in the profession. Our purpose was to prepare female students for their future careers by discussing career planning and management; the complexities of balancing career and family life; and career commitment. The technique of structured role-model analysis was used to encourage students to seek out, listen to, and learn from successful role-models. This technique enabled students to identify recurrent themes, advice and strategies among successful pharmacists who participated as guest speakers. Students were assisted in formulating their own career plans and developing a strategy for accomplishment. Courses of this type can increase a young woman's sophistication as she enters the profession and enable her to make more intelligent career decisions.

Curriculum↗
PubMed1998

Prognoses of multiparametric medical time courses applied to kidney function assessments.

In this paper, we describe an approach to utilize Case-Based Reasoning methods for trend prognoses for the monitoring of the kidney function in an Intensive Care Unit (ICU) setting. Since using conventional methods for reasoning over time does not fit for course predictions with poor medical knowledge of typical course patterns, we have developed abstraction methods suitable for integration into our Case-Based Reasoning system ICONS. These methods combine medical experience with prognoses of multiparametric courses. On the ICU, the monitoring system NIMON provides a daily report based on current measured and calculated kidney function parameters. We subsequently generate course-characteristic trend descriptions of the renal function over the course of time. Using Case-Based Reasoning retrieval methods, we search in the case base for courses similar to the current trend descriptions. Finally, we present the current course together with similar courses as comparisons and as possible prognoses to the user. We applied Case-Based Reasoning methods in a domain which seemed reserved for statistical methods and conventional temporal reasoning.

Artificial Intelligence↗
PubMed1999

Selecting a rehabilitation program for people with stroke.

This article reviews the 1997 Balanced Budget Act as it pertains to Medicare reimbursement and its consequent impact on medical rehabilitation in general and on persons with stroke in particular. Following a description of the concept and practice of "consumer choice" in health care today, the author frames "choice" in the context of outcomes management wherein the person with stroke may be provided with a report card that describes what outcomes the patient might expect following a course of rehabilitation. Today more than ever, patients are beginning to require information about provider performance that is easy to understand and allows for them to make intelligent purchasing decisions. Literature is reviewed that documents better stroke outcomes in specific types of rehabilitation settings. Finally, a variety of existing consumer tools are reviewed that assist the person with stroke in making an enlightened choice for an optimal setting for stroke rehabilitation. Unfortunately, persons with stroke may not consistently be able to exercise an educated choice because the payer may independently determine placement. An extensive consumer check list of quality indicators is provided to enable the patient's family and provider to evaluate the appropriateness of placing a person with stroke in a given setting.

Choice Behavior↗