Yazar "Oner, Zulal" seçeneğine göre listele

Listeleniyor 1 - 6 / 6
  • Küçük Resim
    Öğe
    Analysis of the effects of total pneumatized turbinate volume on septum deviation, maxillary sinus volume, and maxillopalatal parameters: A multidetector computerized tomography study
    (Wolters Kluwer Medknow Publications, 2023) Senol, Deniz; Oner, Serkan; Secgin, Yusuf; Oner, Zulal; Toy, Seyma
    Introduction: The aim of this study was to examine the effects of pneumatized turbinate volume (PTV) on nasal septum deviation (NSD), maxillary sinus volume (MSV), and maxillopalatal parameters with multidetector computed tomography (MDCT). Material and Methods: MDCT images of a total of 73 patients (35 females and 38 males) between the ages of 25 and 58 years were used in the study. PTV, MSV, and NSD angle and direction and interalveolar distance (IAD), maxillary spin distance (MSD), and maxillopalatal angle (MPA) measurements were made on images brought to the orthogonal plane in 3 plans. Results: Turbinate pneumatization (superior, middle, or inferior) was found in a total of 55 (75.3%) patients (28 females and 27 males). The number of patients with turbinate pneumatization on the right side was 14 (19.2%), while the number of patients with turbinate pneumatization on the left side was 15 (20.5%) and the number of bilateral pneumatization was 26 (35.6%). While no significant association was found between the presence of turbinate pneumatization and septal deviation angle, MSV, MPA, IAD, and MSD measurements, a significant difference was found between the groups in terms of PTV (P < 0.05). No significant association was found between NSD direction and all parameters. Discussion and Conclusion: In this study, we conducted with MDCT images, in addition to the highest incidence in turbinate pneumatization with 75.3%; it was found that PTV did not have an effect on NSD amount, MSV, and maxillopalatal parameters. Men were found to have higher NSD angle, higher maxillary sinus aeration, and larger IAD when compared with women.
  • Küçük Resim
    Öğe
    Can Typical Cervical Vertebrae Be Distinguished from One Another by Using Machine Learning Algorithms? Radioanatomic New Markers
    (Duzce Univ, Fac Medicine, 2023) Senol, Deniz; Secgin, Yusuf; Toy, Seyma; Oner, Serkan; Oner, Zulal
    Objective: The aim of this study is to distinguish the typical cervical vertebrae that cannot be separated from one another with the naked eye by using machine algorithms (ML) with measurements made on computerized tomography (CT) images and to show the differences of these vertebrae.Methods: This study was conducted by examining the 536 typical cervical vertebrae CT images of 134 (between the ages of 20 and 55) individuals. Measurements of cervical vertebrae were made on coronal, axial and sagittal section. 6 different combinations (Group 1: C3 - C4, Group 2: C3 - C5, Group 3: C3 - C6, Group 4: C4 - C5, Group 5: C4 - C6, Group 6: C5 - C6) were formed with parameters of each vertebrae and they were analyzed in ML algorithms. Accuracy (Acc), Matthews correlation coefficient (Mcc), Specificity (Spe), Sensitivity (Sen) values were obtained as a result of the analysis.Results: As a result of this study, the highest success was obtained with Linear Discriminant Analysis (LDA) and Logistic Regression (LR) algorithms. The highest Acc rate was found as 0.94 with LDA and LR algorithm in Groups 3 and Group 4, the highest Spe value was found as 0.95 with LDA and LR algorithm in Group 5, the highest Mcc value was found as 0.90 with LDA and LR algorithm in Group 5 and the highest Sen value was found as 0.94 with LDA and LR algorithm in Groups 3 and 5. Conclusions: As a conclusion, it was found that typical cervical vertebrae can be distinguished from each other with high accuracy by using ML algorithms.
  • Küçük Resim Yok
    Öğe
    Evaluation of Oxidative System Parameters in Alzheimer's Disease Before Medical Treatment
    (Taiwan Soc Geriatric Emergency & Critical Care Medicine-Tsgecm, 2022) Ayada, Ceylan; Erbay, Umran Toru; Korkut, Yasemin; Guleken, Zozan; Oner, Zulal
    Background: Alzheimer's disease (AD) is the most common reason for dementia and is one of the most important causes of morbidity and mortality in the aging population. A crucial component of AD is the brain's sensitivity to oxidative stress. We aimed to determine the oxidative load of patients with AD who had just been diagnosed and had not yet begun medical treatment.Methods: To assess oxidative load before drug administration, we compared the levels of serum total antioxidant (TAS), oxidant status (TOS), paraoxonase (PON1), arylesterase (ARES), total thiol (THIOL) levels in patients just diagnosed with AD (n = 41) and control (n = 45) with the totally 86 individuals. AD and control groups oxidative stress index (OSI) ratio was calculated too.Results: There was a statistically significant difference between the AD and control groups for mean TAS, TOS, and OSI levels with a 95% confidence level (pTAS = 0.001, pTOS = 0.005, pOSI = 0.001). There was not a statistically significant difference between the groups in terms of mean PON1, ARES, and THIOL values. Significantly negative and positive correlations were found for the interested parameters in both groups.Conclusion: The increase in antioxidative capacity in patients with AD may be related to ARES supported by TAS, and THIOL levels suggest, that those protein oxidation mechanisms are effective in the progress of AD disease before medication.Copyright (c) 2022, Taiwan Society of Geriatric Emergency & Critical Care Medicine.
  • Küçük Resim Yok
    Öğe
    Gender prediction with the parameters obtained from pelvis computed tomography images and machine learning algorithms
    (Wolters Kluwer Medknow Publications, 2022) Secgin, Yusuf; Oner, Zulal; Turan, Muhammed Kamil; Oner, Serkan
    Introduction: In the skeletal system, the most dimorphic bones employed for postmortem gender prediction include the bones in the pelvic skeleton. Bone measurements are usually conducted with cadaver bones. Computed tomography (CT) is an increasingly popular method due to its ease of use, reconstruction opportunities, and lower impact of age bias and provides a modern data source. Even when parameters obtained with different or same bones are missing, machine learning (ML) algorithms allow the use of statistical methods to predict gender. This study was carried out in order to obtain high accuracy in estimating gender with the pelvis skeleton by integrating ML algorithms, which are used extensively in the field of engineering, in the field of health. Material and Methods: In the present study, pelvic CT images of 300 healthy individuals (150 females, 150 males) between the ages of 25 and 50 (the mean female age = 40, the mean male age = 37) were transformed into orthogonal images, and landmarks were placed on promontory, iliac crest, sacroiliac joint, anterior superior iliac spine, anterior inferior iliac spine, terminal line, obturator foramen, greater trochanter, lesser trochanter, femoral head, femoral neck, body of femur, ischial tuberosity, acetabulum, and pubic symphysis, and coordinates of these regions were obtained. Four groups were formed based on various angle and length combinations obtained from these coordinates. These four groups were analyzed with ML algorithms such as Logistic Regression, Linear Discriminant Analysis (LDA), Random Forest, Extra Trees Classifier, and ADA Boost Classifier. Results: In the analysis, it was determined that the highest accuracy was 0.96 (sensitivity 0.95, specificity 0.97, Matthew's Correlation Coefficient 0.93) with LDA. Discussion and Conclusion: The use of length and angle measurements obtained from the pelvis showed that the LDA model was effective in estimating gender.
  • Küçük Resim
    Öğe
    An MRI Analysis of the Lumbar Lordosis Angle and Lumbar Muscle Thicknesses in Patients with Non-Specific Low Back Pain
    (Duzce Univ, Fac Medicine, 2023) Dagli, Ali Cihan; Oner, Serkan; Oner, Zulal; Dagli, Beyza Yazgan
    Objective: This study aimed to examine the relationship of lumbar lordosis angle and lumbar muscle thickness with non-specific low back pain (LBP) through magnetic resonance imaging (MRI) images.Methods: The study included 96 individuals (43 men/53 women) aged between 18-65 with non-specific LBP that is not explained by disc pathology based on MRI, who applied to affiliated Training and Research Hospital with the complaint of LBP between March-June 2019. Sociodemographic information was recorded using an LBP assessment form. The Oswestry LBP Disability Questionnaire was used for LBP disability. The thicknesses of muscle (m.) psoas major, m. multifidus, m. quadratus lumborum and m. erector spinae were measured corresponding to the L3-L4 vertebral level by using Radiant DICOM viewer program. The Cobb Angle method was used for lumbar lordosis angle determination. Measurements were made in three repetitions using the Radiant DICOM viewer program. Results: The results showed that an inverse relationship was found between the Oswestry Disability Index (ODI) and m. psoas major thickness (p<0.05). Given the comparison of right -left side muscle thicknesses, left side muscles were thicker (p<0.05). There were no significant differences observed between males and females in terms of lumbar lordosis angle (LLA). However, in terms of muscle thickness, males exhibited higher values, except for the transverse measurements of the right quadratus lumborum and left erector spinae muscles, which showed no significant differences (p < 0.05). Furthermore, a positive correlation was found between LLA and the transverse thickness of the left psoas major muscle (p = 0.034) and the anterior-posterior thickness of the bilateral erector spinae muscles (p < 0.001).Conclusions: In regard to inverse relationship between m. psoas major thickness and ODI, m. psoas major should be taken into consideration to alleviate the disability caused by LBP. Additionally, the difference on both sides is likely one of the causes of muscle imbalance, and this might be one of the reasons for LBP, thereby causing disability in daily tasks due to LBP.
  • Küçük Resim
    Öğe
    Sex and age estimation with machine learning algorithms with parameters obtained from cone beam computed tomography images of maxillary first molar and canine teeth
    (Int Assoc Law & Forensic Sciences, 2023) Senol, Deniz; Secgin, Yusuf; Duman, Burak Suayip; Toy, Seyma; Oner, Zulal
    BackgroundThe aim of this study is to obtain a highly accurate and objective sex and age estimation by using the parameters of maxillary molar and canine teeth obtained from cone beam computed tomography images in the input of machine learning algorithms. Cone beam computed tomography images of 240 people aged between 25 and 54 were randomly selected from the archive systems of the hospital and transferred to Horos Medikal. 3D curved multiplanar reconstruction was applied to these images and a 3D image was obtained. The resulting image was brought to the orthogonal plane and the measurements were made by superimposing them.ResultsThe results were grouped in four different age groups (25-30, 31-36, 37-49, 50-54) and recorded. As a result of our study, the highest accuracy rate was found as 0.81 in sex estimation with ADA Boost Classifier algorithm, while in age estimation, the highest accuracy rate was found as 0.84 between 25-30 and 31-36 age groups with random forest algorithm, as 0.74 between 25-30 and 37-49 age groups with random forest and ADA Boost Classifier algorithms and as 0.85 between 25-30 and 50-54 age groups with random forest algorithm.ConclusionsOur study differs from other studies in two aspects; the first is the selection of a sensitive method such as cone beam computed tomography, and the second is the selection of machine learning algorithms. As a result of our study, the highest accuracy rate was found as 0.81 in sex estimation and as 0.85 in age estimation with parameters of maxillary canine and molar teeth.