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Yuh-Feng Wang

Publications and source records attributed to Yuh-Feng Wang.

7 recordsLinked to original sources
PubMed2006

Prediction of target range of intact parathyroid hormone in hemodialysis patients with artificial neural network.

The application of artificial neural network (ANN) to predict outcome and explore potential relationships among clinical data is increasing being used in many clinical scenarios. The aim of this study was to validate whether an ANN is a useful tool for predicting the target range of plasma intact parathyroid hormone (iPTH) concentration in hemodialysis patients. An ANN was constructed with input variables collected retrospectively from an internal validation group (n = 129) of hemodialysis patients. Plasma iPTH was the dichotomous outcome variable, either target group (150 ng/L 300 ng/L). After internal validation, the ANN was prospectively tested in an external validation group (n = 32) of hemodialysis patients. The final ANN was a multilayer perceptron network with six predictors including age, diabetes, hypertension, and blood biochemistries (hemoglobin, albumin, calcium). The externally validated ANN provided excellent discrimination as appraised by area under the receiver operating characteristic curve (0.83 +/- 0.11, p = 0.003). The Hosmer-Lemeshow statistic was 5.02 (p= 0.08 > 0.05) which represented a good-fit calibration. These results suggest that an ANN, which is based on limited clinical data, is able to accurately forecast the target range of plasma iPTH concentration in hemodialysis patients.

Female↗
PubMed2006

Application of upper extremity radionuclide venography as a diagnostic approach for Port-A catheter thrombosis.

BACKGROUND: To investigate the role of upper extremity radionuclide venography as a potential diagnostic modality in the assessment of venous thrombosis associated with a Port-A catheter. METHODS: Fourteen symptomatic patients who had received Port-A catheter implantation were enrolled. A dynamic nuclear medicine flow study was performed with intravenous administration of Technetium-99m macroaggregated albumin to both upper extremities. Imaging patterns of the venous system were categorized as patency, partial obstruction, and total occlusion. RESULTS: The findings of the dynamic images clearly demonstrated clinical problems. Three patients were free of a definite venous flow change. Three patients had partial obstruction of venous return. A significant cut-off of venous return was demonstrated in 8 patients, and total occlusions were hence diagnosed. All patients underwent this procedure smoothly without any complication. CONCLUSION: These results suggest that upper extremity radionuclide venography is an easily performed and effective method for diagnosing Port-A catheter thrombosis in clinical practice.

Adult↗
PubMed2006

Applying an artificial neural network to predict osteoporosis in the elderly.

Osteoporosis is an essential index of health and economics in every country. Recognizing asymptomatic elderly population with high risks of osteoporosis remains a difficult challenge. For this purpose, we developed and validated an artificial neural network (ANN) to identify the osteoporotic subjects in the elderly. The study population consisted of 1403 elderly adults (mean age 63.50 +/- 0.24 years ranged from 50 to 91 years old, 157 male and 1246 female) randomly selected into 3 sets, 703 participants in training set, 350 participants in selection set, and the remaining 350 participants in test set. The input variables included demographic characteristics, anthropometric measurements, and clinical data. The outcome variable was dichotomous, either non-osteoporotic (T-score of greater than -2.5) or osteoporotic (T-score of -2.5 or less) groups classified by the measurement from dual energy X-ray absorptiometry. ANN was constructed with data from training and selection sets and validated in test set whose outcome variable was unknown to the network. The performance of ANN was evaluated by discrimination and calibration simultaneously. After training processes, the final best ANN was a multilayer perceptron network which determined seven input variables (gender, age, weight, height, body mass index, postmenopausal status, and coffee consumption) as significant features. The discriminatory power of ANN for test set was excellent (area under receiver operating characteristics curve = 0.82 +/- 0.03). ANN also had statistically good fit represented by statistically insignificant Hosmer-Lemeshow statistic (p = 0.24). These results suggested that our final ANN concurrently had good discriminatory power and good-fit calibration. ANN can be used as a promising tool for the elderly to stratify high risk subjects into osteoporotic group.

Aged↗
PubMed2005

Applying an artificial neural network to predict total body water in hemodialysis patients.

BACKGROUND: Estimating total body water (TBW) is crucial in determining dry weight and dialytic dose for hemodialysis patients. Several anthropometric equations have been used to predict TBW, but a more accurate method is needed. We developed an artificial neural network (ANN) to predict TBW in hemodialysis patients. METHODS: Demographic data, anthropometric measurements, and multifrequency bioelectrical impedance analysis (MF-BIA) were investigated in 54 patients. TBW measured by MF-BIA (TBW-BIA) was the reference. The predictive value of TBW based on ANN and five anthropometric equations (58% of actual body weight, Watson formula, Hume formula, Chertow formula, and Lee formula) was evaluated. RESULTS: Predictive TBW values derived from anthropometric equations were significantly higher than TBW-BIA (31.341 +/- 6.033 liters). The only non-significant difference was between TBW-ANN (31.468 +/- 5.301 liters) and TBW-BIA (p = 0.639). ANN had the strongest Pearson's correlation coefficient (0.911) and smallest root mean square error (2.480); its peak centered most closely to zero with the shortest tails in an empirical cumulative distribution plot when compared with the other five equations. CONCLUSION: ANN could surpass traditional anthropometric equations and serve as a feasible alternative method of TBW estimation for chronic hemodialysis patients.

Adult↗