Biomedical subjects

R N Shiffman

Publications and source records attributed to R N Shiffman.

3 recordsLinked to original sources

PubMed1992

Rule set reduction using augmented decision table and semantic subsumption techniques: application to cholesterol guidelines.

Clinical practice guidelines must comprehensively address all logically possible situations, but this completeness may result in sizable and cumbersome rule sets. We applied rule set reduction techniques to a 576-rule set regarding recommendations for medication treatment of hypercholesterolemia. Using decision tables augmented with information regarding test costs and rule application frequencies, we sorted the rule sets prior to identifying irrelevant tests and eliminating unnecessary rules. Alternatively, we examined the semantic relationships among risk factors in hypercholesterolemia and applied a subsumption technique to reduce the rule set. Both methodologies resulted in substantial rule set compression (mean, 48-70%). Subsumption techniques proved superior for compacting a large rule set based on risk factors.

Adult↗

PubMed1991

Composing user models through logic analysis.

The evaluation of tutorial strategies, interface designs, and courseware content is an area of active research in the medical education community. Many of the evaluation techniques that have been developed (e.g., program instrumentation), commonly produce data that are difficult to decipher or to interpret effectively. We have explored the use of decision tables to automatically simplify and categorize data for the composition of user models--descriptions of student's learning styles and preferences. An approach to user modeling that is based on decision tables has numerous advantages compared with traditional manual techniques or methods that rely on rule-based expert systems or neural networks. Decision tables provide a mechanism whereby overwhelming quantities of data can be condensed into an easily interpreted and manipulated form. Compared with conventional rule-based expert systems, decision tables are more amenable to modification. Unlike classification systems based on neural networks, the entries in decision tables are readily available for inspection and manipulation. Decision tables, descriptions of observations of behavior, also provide automatic checks for ambiguity in the tracking data.

Decision Making↗

PubMed1991

Use of augmented decision tables to convert probabilistic data into clinical algorithms for the diagnosis of appendicitis.

Decision table techniques have been shown to be useful for ensuring logical completeness, eliminating ambiguity, and optimizing the translation of logic into flowcharts or computer programs. Nevertheless, they have not been widely applied in medicine. We have used decision table techniques to demonstrate the derivation of two sets of rules for determining whether to operate on patients with suspected appendicitis based on patterns of observed signs and symptoms. One rule set is based on a diagnostic threshold whereby morbidity is minimized; the other rule set minimizes mortality. For this purpose, we have developed an augmented decision table format that allows the incorporation of probability and utility data.

Algorithms↗