Using decision-tree classifier systems to extract knowledge from databases

One difficulty in applying artificial intelligence techniques to the solution of real world problems is that the development and maintenance of many AI systems, such as those used in diagnostics, require large amounts of human resources. At the same time, databases frequently exist which contain information about the process(es) of interest. Recently, efforts to reduce development and maintenance costs of AI systems have focused on using machine learning techniques to extract knowledge from existing databases. Research is described in the area of knowledge extraction using a class of machine learning techniques called decision-tree classifier systems. Results of this research suggest ways of performing knowledge extraction which may be applied in numerous situations. In addition, a measurement called the concept strength metric (CSM) is described which can be used to determine how well the resulting decision tree can differentiate between the concepts it has learned. The CSM can be used to determine whether or not additional knowledge needs to be extracted from the database. An experiment involving real world data is presented to illustrate the concepts described

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base

Contemporary outcome measures in acute stroke research: choice of primary outcome measure

BACKGROUND AND PURPOSE: The diversity of available outcome measures for acute stroke trials is challenging and implies that the scales may be imperfect. To assist researchers planning trials and to aid interpretation, this article reviews and makes recommendations on the available choices of scales. The aim is to identify an approach that will be universally accepted and that should be included in most acute trials, without seeking to restrict options for special circumstances. METHODS: The article considers outcome measures that have been widely used or are currently advised. It examines desirable properties for outcome measures such as validity, relevance, responsiveness, statistical properties, availability of training, cultural and language issues, resistance to comorbidity, as well as potential weaknesses. Tracking and agreement among outcomes are covered. RESULTS: Typical ranges of scores for the common scales are described, along with their statistical properties, which in turn influence optimal analytic techniques. The timing of recovery on scores and usual practice in trial design are considered. CONCLUSIONS: The preferred outcome measure for acute trials is the modified Rankin Scale, assessed at 3 months after stroke onset or later. The interview should be conducted by a certified rater and should involve both the patient and any relevant caregiver. Incremental benefits at any level of the modified Rankin Scale may be acceptable. The modified Rankin Scale is imperfect but should be retained in its present form for comparability with existing treatment comparisons. No second measure should be required, but correlations with supporting scales may be used to confirm consistency in direction of effects on other measures

Stroke outcome in clinical trial patients deriving from different countries

<p><b>Background and Purpose:</b> Stroke incidence and outcome vary widely within and across geographical locations. We examined whether differences in index stroke severity, stroke risk factors, mortality, and stroke outcome across geographical locations remain after adjusting for case mix.</p> <p><b>Methods:</b> We analyzed 3284 patients from the Virtual International Stroke Trials Archive (VISTA). We used logistic regression to examine the incidence of mild index stroke, functional, and neurological outcomes after accounting for age, medical history, year of trial recruitment, and initial stroke severity in the functional and neurological outcome analyses. We examined mortality between geographical regions using a Cox proportional hazards model, accounting for age, initial stroke severity, medical history, and year of trial recruitment.</p> <p><b>Results</b> Patients enrolled in the USA and Canada had the most severe index strokes. Those recruited in Austria and Switzerland had the best functional and neurological outcomes at 90 days (P<0.05), whereas those enrolled in Germany had the worst functional outcome at 90 days (P=0.013). Patients enrolled in Austria, Switzerland, Belgium, Netherlands, Finland, Germany, Greece, Israel, Spain, and Portugal had a significantly better survival rate when compared with those enrolled in USA and Canada. Patients enrolled in trials after 1998 had more severe index strokes, with no significant difference in outcome compared with those enrolled before 1998.</p> <p><b>Conclusion:</b> We identified regional variations in index stroke severity, outcome, and mortality for patients enrolled in ischemic stroke clinical trials over the past 13 years that were not fully explained by case mix. Index stroke severity was greater in patients enrolled after 1998, with no significant improvement in outcomes compared to those enrolled before 1998.</p&gt

Mismatch-based delayed thrombolysis: a meta-analysis

<p><b>Background and Purpose</b>: Clinical benefit from thrombolysis is reduced as stroke onset to treatment time increases. The use of "mismatch" imaging to identify patients for delayed treatment has face validity and has been used in case series and clinical trials. We undertook a meta-analysis of relevant trials to examine whether present evidence supports delayed thrombolysis among patients selected according to mismatch criteria.</p> <p><b>Methods</b>: We collated outcome data for patients who were enrolled after 3 hours of stroke onset in thrombolysis trials and had mismatch on pretreatment imaging. We selected the trials on the basis of a systematic search of the Web of Knowledge. We compared favorable outcome, reperfusion and/or recanalization, mortality, and symptomatic intracerebral hemorrhage between the thrombolyzed and nonthrombolyzed groups of patients and the probability of a favorable outcome among patients with successful reperfusion and clinical findings for 3 to 6 versus 6 to 9 hours from poststroke onset. Results are expressed as adjusted odds ratios (a-ORs) with 95% CIs. Heterogeneity was explored by test statistics for clinical heterogeneity, I2 (inconsistency), and L’Abbé plot.</p> <p><b>Results</b>: We identified articles describing the DIAS, DIAS II, DEDAS, DEFUSE, and EPITHET trials, giving a total of 502 mismatch patients thrombolyzed beyond 3 hours. The combined a-ORs for favorable outcomes were greater for patients who had successful reperfusion (a-OR=5.2; 95% CI, 3 to 9; I2=0%). Favorable clinical outcome was not significantly improved by thrombolysis (a-OR=1.3; 95% CI, 0.8 to 2.0; I2=20.9%). Odds for reperfusion/recanalization were increased among patients who received thrombolytic therapy (a-OR=3.0; 95% CI, 1.6 to 5.8; I2=25.7%). The combined data showed a significant increase in mortality after thrombolysis (a-OR=2.4; 95% CI, 1.2 to 4.9; I2=0%), but this was not confirmed when we excluded data from desmoteplase doses that were abandoned in clinical development (a-OR=1.6; 95% CI, 0.7 to 3.7; I2=0%). Symptomatic intracerebral hemorrhage was significantly increased after thrombolysis (a-OR=6.5; 95% CI, 1.2 to 35.4; I2=0%) but not significant after exclusion of abandoned doses of desmoteplase (a-OR=5.4; 95% CI, 0.9 to 31.8; I2=0%).</p> <p><b>Conclusions</b>: Delayed thrombolysis amongst patients selected according to mismatch imaging is associated with increased reperfusion/recanalization. Recanalization/reperfusion is associated with improved outcomes. However, delayed thrombolysis in mismatch patients was not confirmed to improve clinical outcome, although a useful clinical benefit remains possible. Thrombolysis carries a significant risk of symptomatic intracerebral hemorrhage and possibly increased mortality. Criteria to diagnose mismatch are still evolving. Validation of the mismatch selection paradigm is required with a phase III trial. Pending these results, delayed treatment, even according to mismatch selection, cannot be recommended as part of routine care.</p&gt

Evolution of the Thrombolytic Treatment Window for Acute Ischemic Stroke

Ischemic stroke is a major cause of morbidity and mortality for which the only approved treatment in the acute setting is intravenous thrombolysis. The efficacy and safety of recombinant tissue plasminogen activator (rt-PA) have been firmly established within 3 h of symptom onset; however, few patients are eligible for treatment in this time window. Expanding the time for treatment has been challenging, but new evidence has demonstrated a modest statistical improvement in selected patients when rt-PA is administered within 4.5 h. This important finding hopefully will enable more patients to receive treatment and simultaneously provides an opportunity to reaffirm that the benefits of rt-PA diminish with time