ABSTRACT
UNLABELLED: Screening laboratory tests for thyroid disease often include serum levels for thyroxine (T4), thyrotropic hormone (TSH), and triiodothyronine resin binding (T3) as a measure of T4 binding to serum. A neural network using the above values as input was unable to converge during training to identify an output diagnoses of six common thyroid functional states. When binding protein (TBG) data were supplied the network readily converged. Since thyroxine binding can be roughly estimated from a relationship between T4 and T3, a virtual input node reflecting the binding was calculated from each T4/T3 input set and used as additional input. With this addition, the system trained easily and accurately diagnosed from the training set. CONCLUSION: 1) Quantitative laboratory data can be used in input neurodes in a diagnostic network 2) Training and diagnostic accuracy for the network is more efficient using the virtual TBG neurode than by either omitting TBG data or using actual TBG values.
Subject(s)
Diagnosis, Computer-Assisted , Neural Networks, Computer , Thyroid Diseases/diagnosis , Humans , Thyroid Diseases/blood , Thyrotropin/blood , Thyroxine/blood , Thyroxine-Binding Proteins/analysis , Triiodothyronine/bloodABSTRACT
Residency training programs in Internal Medicine require resident attendance in a continuity clinic. This inevitably engenders conflicts between scheduling in the ambulatory clinic and the required teaching activities of the in-patient services. Some of the conflicts can be resolved by allowing the in-patient service directors to indicate preferred plans for their residents to attend in the continuity clinic. With this plan, scheduling becomes quite complicated. A computer program is presented with coordinates these service requests with ambulatory clinic scheduling. As a result, a given resident may have his/her clinic day changed on different rotations. The program automatically arbitrates conflicts and publishes the attendance dates for the entire academic year. This information is supplied to the appointment desk so that patients can be scheduled accordingly. This system has resulted in a 74% continuity rate and improved satisfaction by both residents and staff.
