{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/42156"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/42156","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Predicting drug interactions with a three level causal model","abstract":"A medical expert system for predicting qualitative pharmacodynamic interactions of the cardiovascular system is described. TLCM traces causal paths of drug action through up to three levels of drug action. The three levels which are molecular/receptor level, physiological level and clinical level provide both deep and shallow reasoning in order to overcome the problem of unknowns in medical expert systems. Sparsity of information in pharmacology results from necessity of using non-invasive techniques for monitoring drug effects in the human subject and difficulty in isolating effect from feedback. The qualitative nature of TLCM is another attempt to deal with incomplete information in pharmacology.","abstract_html":"A medical expert system for predicting qualitative pharmacodynamic interactions of the cardiovascular system is described. TLCM traces causal paths of drug action through up to three levels of drug action. The three levels which are molecular/receptor level, physiological level and clinical level provide both deep and shallow reasoning in order to overcome the problem of unknowns in medical expert systems. Sparsity of information in pharmacology results from necessity of using non-invasive techniques for monitoring drug effects in the human subject and difficulty in isolating effect from feedback. The qualitative nature of TLCM is another attempt to deal with incomplete information in pharmacology.","abstract_has_math":false,"creators":["Scheckler, Rebecca Klein"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Computer Science","degree_department":"Computer Science","school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1990,"date_issued":"1990","date_published":"1990","updated_at":"2026-07-22T22:20:25Z","subjects":[],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-04182009-041422"],"render_values":[{"text":"etd-04182009-041422","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/42156","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Computer Science"]},{"key":"dc:creator","label":"Author","values":["Scheckler, Rebecca Klein"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:34:14Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:34:14Z","2009-04-18"]},{"key":"dc:date.issued","label":"Date","values":["1990"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-04182009-041422"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/42156"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A medical expert system for predicting qualitative pharmacodynamic interactions of the cardiovascular system is described. TLCM traces causal paths of drug action through up to three levels of drug action. The three levels which are molecular/receptor level, physiological level and clinical level provide both deep and shallow reasoning in order to overcome the problem of unknowns in medical expert systems. Sparsity of information in pharmacology results from necessity of using non-invasive techniques for monitoring drug effects in the human subject and difficulty in isolating effect from feedback. The qualitative nature of TLCM is another attempt to deal with incomplete information in pharmacology."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["BTD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Predicting drug interactions with a three level causal model"]}]}],"canonical_facts":{"dc:contributor.department":["Computer Science"],"dc:creator":["Scheckler, Rebecca Klein"],"dc:date.accessioned":["2014-03-14T21:34:14Z"],"dc:date.available":["2014-03-14T21:34:14Z","2009-04-18"],"dc:date.issued":["1990"],"dc:description.abstract":["A medical expert system for predicting qualitative pharmacodynamic interactions of the cardiovascular system is described. TLCM traces causal paths of drug action through up to three levels of drug action. The three levels which are molecular/receptor level, physiological level and clinical level provide both deep and shallow reasoning in order to overcome the problem of unknowns in medical expert systems. Sparsity of information in pharmacology results from necessity of using non-invasive techniques for monitoring drug effects in the human subject and difficulty in isolating effect from feedback. The qualitative nature of TLCM is another attempt to deal with incomplete information in pharmacology."],"dc:description.degree":["Master of Science"],"dc:format.medium":["BTD"],"dc:format.mimetype":["application/pdf"],"dc:identifier.other":["etd-04182009-041422"],"dc:identifier.uri":["http://hdl.handle.net/10919/42156"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Predicting drug interactions with a three level causal model"],"dc:type":["Thesis"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:25Z"}