1.Prediction of Serum Creatinine in Hemodialysis Patients Using a Kernel Approach for Longitudinal Data
Mohammad Moqaddasi AMIRI ; Leili TAPAK ; Javad FARADMAL ; Javad HOSSEINI ; Ghodratollah ROSHANAEI
Healthcare Informatics Research 2020;26(2):112-118
Longitudinal data are prevalent in clinical research; due to their correlated nature, special analysis must be used for this type of data. Creatinine is an important marker in predicting end-stage renal disease, and it is recorded longitudinally. This study compared the prediction performance of linear regression (LR), linear mixed-effects model (LMM), least-squares support vector regression (LS-SVR), and mixed-effects least-squares support vector regression (MLS-SVR) methods to predict serum creatinine as a longitudinal outcome. We used a longitudinal dataset of hemodialysis patients in Hamadan city between 2013 and 2016. To evaluate the performance of the methods in serum creatinine prediction, the data was divided into two sets of training and testing samples. Then LR, LMM, LS-SVR, and MLS-SVR were fitted. The prediction performance was assessed and compared in terms of mean squared error (MSE), mean absolute error (MAE), mean absolute prediction error (MAPE), and determination coefficient ( The MLS-SVR outperformed the other methods in terms of the least prediction error; MSE = 1.280, MAE = 0.833, and MAPE = 0.129 for the training set and MSE = 3.275, MAE = 1.319, and MAPE = 0.159 for the testing set. Also, the MLS-SVR had the highest The MLS-SVR achieved the best serum creatinine prediction performance in comparison to LR, LMM, and LS-SVR.
2.Correlations between anatomical variations of the nasal cavity and ethmoidal sinuses on cone-beam computed tomography scans
Abbas SHOKRI ; Mohammad Javad FARADMAL ; Bahareh HEKMAT
Imaging Science in Dentistry 2019;49(2):103-113
PURPOSE: Anatomical variations of the external nasal wall are highly important, since they play a role in obstruction or drainage of the ostiomeatal complex and ventilation and can consequently elevate the risk of pathological sinus conditions. This study aimed to assess anatomical variations of the nasal cavity and ethmoidal sinuses and their correlations on cone-beam computed tomography (CBCT) scans. MATERIALS AND METHODS: This cross-sectional study evaluated CBCT scans of 250 patients, including 107 males and 143 females, to determine the prevalence of anatomical variations of the nasal cavity and ethmoidal sinuses. All images were taken using a New Tom 3G scanner. Data were analyzed using the chi-square test, Kruskal-Wallis test, and the Mann-Whitney test. RESULTS: The most common anatomical variations were found to be nasal septal deviation (90.4%), agger nasi air cell (53.6%), superior orbital cell (47.6%), pneumatized nasal septum (40%), and Onodi air cell (37.2%). Correlations were found between nasal septal deviation and the presence of a pneumatized nasal septum, nasal spur, and Haller cell. No significant associations were noted between the age or sex of patients and the presence of anatomical variations (P>0.05). CONCLUSION: Radiologists and surgeons must pay close attention to the anatomical variations of the sinonasal region in the preoperative assessment to prevent perioperative complications.
Cone-Beam Computed Tomography
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Cross-Sectional Studies
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Drainage
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Ethmoid Sinus
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Female
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Humans
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Male
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Nasal Cavity
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Nasal Septum
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Orbit
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Prevalence
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Surgeons
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Ventilation
Result Analysis
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