TY - GEN
T1 - Experienced physicians and automatic generation of decision rules from clinical data
AU - Klement, William
AU - Wilk, Szymon
AU - Michalowski, Martin
AU - Farion, Ken
PY - 2010
Y1 - 2010
N2 - Clinical Decision Support Systems embed data-driven decision models designed to represent clinical acumen of an experienced physician. We argue that eliminating physicians' diagnostic biases from data improves the overall quality of concepts, which we represent as decision rules. Experiments conducted on prospectively collected clinical data show that analyzing this filtered data produces rules with better coverage, certainty and confirmation. Cross-validation testing shows improvement in classification performance.
AB - Clinical Decision Support Systems embed data-driven decision models designed to represent clinical acumen of an experienced physician. We argue that eliminating physicians' diagnostic biases from data improves the overall quality of concepts, which we represent as decision rules. Experiments conducted on prospectively collected clinical data show that analyzing this filtered data produces rules with better coverage, certainty and confirmation. Cross-validation testing shows improvement in classification performance.
UR - https://www.scopus.com/pages/publications/79956261006
UR - https://www.scopus.com/pages/publications/79956261006#tab=citedBy
U2 - 10.1007/978-3-642-13529-3_23
DO - 10.1007/978-3-642-13529-3_23
M3 - Conference contribution
AN - SCOPUS:79956261006
SN - 3642135285
SN - 9783642135286
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 207
EP - 216
BT - Rough Sets and Current Trends in Computing - 7th International Conference, RSCTC 2010, Proceedings
T2 - 7th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2010
Y2 - 28 June 2010 through 30 June 2010
ER -