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1. Leveraging Object Priors for Point Tracking

Author

Boote, Bikram, Thai, Anh, Jia, Wenqi, Kara, Ozgur, Stojanov, Stefan, Rehg, James M., and Lee, Sangmin

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Robotics
Abstract

Point tracking is a fundamental problem in computer vision with numerous applications in AR and robotics. A common failure mode in long-term point tracking occurs when the predicted point leaves the object it belongs to and lands on the background or another object. We identify this as the failure to correctly capture objectness properties in learning to track. To address this limitation of prior work, we propose a novel objectness regularization approach that guides points to be aware of object priors by forcing them to stay inside the the boundaries of object instances. By capturing objectness cues at training time, we avoid the need to compute object masks during testing. In addition, we leverage contextual attention to enhance the feature representation for capturing objectness at the feature level more effectively. As a result, our approach achieves state-of-the-art performance on three point tracking benchmarks, and we further validate the effectiveness of our components via ablation studies. The source code is available at: https://github.com/RehgLab/tracking_objectness, Comment: ECCV 2024 ILR Workshop

Published
2024

2. Towards Social AI: A Survey on Understanding Social Interactions

Author

Lee, Sangmin, Li, Minzhi, Lai, Bolin, Jia, Wenqi, Ryan, Fiona, Cao, Xu, Kara, Ozgur, Boote, Bikram, Shi, Weiyan, Yang, Diyi, and Rehg, James M.

Subjects
Computer Science - Human-Computer Interaction
Abstract

Social interactions form the foundation of human societies. Artificial intelligence has made significant progress in certain areas, but enabling machines to seamlessly understand social interactions remains an open challenge. It is important to address this gap by endowing machines with social capabilities. We identify three key capabilities needed for effective social understanding: 1) understanding multimodal social cues, 2) understanding multi-party dynamics, and 3) understanding beliefs. Building upon these foundations, we classify and review existing machine learning works on social understanding from the perspectives of verbal, non-verbal, and multimodal social cues. The verbal branch focuses on understanding linguistic signals such as speaker intent, dialogue sentiment, and commonsense reasoning. The non-verbal branch addresses techniques for perceiving social meaning from visual behaviors such as body gestures, gaze patterns, and facial expressions. The multimodal branch covers approaches that integrate verbal and non-verbal multimodal cues to holistically interpret social interactions such as recognizing emotions, conversational dynamics, and social situations. By reviewing the scope and limitations of current approaches and benchmarks, we aim to clarify the development trajectory and illuminate the path towards more comprehensive intelligence for social understanding. We hope this survey will spur further research interest and insights into this area.

Published
2024

3. Transfer Learning for Cross-dataset Isolated Sign Language Recognition in Under-Resourced Datasets

Author

Kindiroglu, Ahmet Alp, Kara, Ozgur, Ozdemir, Ogulcan, and Akarun, Lale

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Sign language recognition (SLR) has recently achieved a breakthrough in performance thanks to deep neural networks trained on large annotated sign datasets. Of the many different sign languages, these annotated datasets are only available for a select few. Since acquiring gloss-level labels on sign language videos is difficult, learning by transferring knowledge from existing annotated sources is useful for recognition in under-resourced sign languages. This study provides a publicly available cross-dataset transfer learning benchmark from two existing public Turkish SLR datasets. We use a temporal graph convolution-based sign language recognition approach to evaluate five supervised transfer learning approaches and experiment with closed-set and partial-set cross-dataset transfer learning. Experiments demonstrate that improvement over finetuning based transfer learning is possible with specialized supervised transfer learning methods., Comment: Accepted to The 18th IEEE International Conference on Automatic Face and Gesture Recognition 2024, Code available in https://github.com/alpk/tid-supervised-transfer-learning-dataset

Published
2024

4. RAVE: Randomized Noise Shuffling for Fast and Consistent Video Editing with Diffusion Models

Author

Kara, Ozgur, Kurtkaya, Bariscan, Yesiltepe, Hidir, Rehg, James M., and Yanardag, Pinar

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recent advancements in diffusion-based models have demonstrated significant success in generating images from text. However, video editing models have not yet reached the same level of visual quality and user control. To address this, we introduce RAVE, a zero-shot video editing method that leverages pre-trained text-to-image diffusion models without additional training. RAVE takes an input video and a text prompt to produce high-quality videos while preserving the original motion and semantic structure. It employs a novel noise shuffling strategy, leveraging spatio-temporal interactions between frames, to produce temporally consistent videos faster than existing methods. It is also efficient in terms of memory requirements, allowing it to handle longer videos. RAVE is capable of a wide range of edits, from local attribute modifications to shape transformations. In order to demonstrate the versatility of RAVE, we create a comprehensive video evaluation dataset ranging from object-focused scenes to complex human activities like dancing and typing, and dynamic scenes featuring swimming fish and boats. Our qualitative and quantitative experiments highlight the effectiveness of RAVE in diverse video editing scenarios compared to existing methods. Our code, dataset and videos can be found in https://rave-video.github.io., Comment: Project webpage: https://rave-video.github.io , Github: http://github.com/rehg-lab/RAVE

Published
2023

9. ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior

Author

Arican, Metin Ersin, Kara, Ozgur, Bredell, Gustav, and Konukoglu, Ender

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recent works show that convolutional neural network (CNN) architectures have a spectral bias towards lower frequencies, which has been leveraged for various image restoration tasks in the Deep Image Prior (DIP) framework. The benefit of the inductive bias the network imposes in the DIP framework depends on the architecture. Therefore, researchers have studied how to automate the search to determine the best-performing model. However, common neural architecture search (NAS) techniques are resource and time-intensive. Moreover, best-performing models are determined for a whole dataset of images instead of for each image independently, which would be prohibitively expensive. In this work, we first show that optimal neural architectures in the DIP framework are image-dependent. Leveraging this insight, we then propose an image-specific NAS strategy for the DIP framework that requires substantially less training than typical NAS approaches, effectively enabling image-specific NAS. We justify the proposed strategy's effectiveness by (1) demonstrating its performance on a NAS Dataset for DIP that includes 522 models from a particular search space (2) conducting extensive experiments on image denoising, inpainting, and super-resolution tasks. Our experiments show that image-specific metrics can reduce the search space to a small cohort of models, of which the best model outperforms current NAS approaches for image restoration. Codes and datasets are available at https://github.com/ozgurkara99/ISNAS-DIP.

Published
2021

11. Molecular Index Modulation using Convolutional Neural Networks

Author

Kara, Ozgur, Yaylali, Gokberk, Pusane, Ali Emre, and Tugcu, Tuna

Subjects
Computer Science - Emerging Technologies, I.5.4
Abstract

As the potential of molecular communication via diffusion (MCvD) systems at nano-scale communication increases, designing molecular schemes robust to the inevitable effects of molecular interference has become of vital importance. There are numerous molecular approaches in literature aiming to mitigate the effects of interference, namely inter-symbol interference. Moreover, for molecular multiple-input-multiple-output systems, interference among antennas, namely inter-link interference, becomes of significance. Inspired by the state-of-the-art performances of machine learning algorithms on making decisions, we propose a novel approach of a convolutional neural network (CNN)-based architecture. The proposed approach is for a uniquely-designed molecular multiple-input-single-output topology in order to alleviate the damaging effects of molecular interference. In this study, we compare the performance of the proposed network with that of an index modulation approach and a symbol-by-symbol maximum likelihood estimation and show that the proposed method yields better performance., Comment: In submission to Elsevier Nano Communication Networks

Published
2021

12. Towards Fair Affective Robotics: Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition

Author

Kara, Ozgur, Churamani, Nikhil, and Gunes, Hatice

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Robotics
Abstract

As affective robots become integral in human life, these agents must be able to fairly evaluate human affective expressions without discriminating against specific demographic groups. Identifying bias in Machine Learning (ML) systems as a critical problem, different approaches have been proposed to mitigate such biases in the models both at data and algorithmic levels. In this work, we propose Continual Learning (CL) as an effective strategy to enhance fairness in Facial Expression Recognition (FER) systems, guarding against biases arising from imbalances in data distributions. We compare different state-of-the-art bias mitigation approaches with CL-based strategies for fairness on expression recognition and Action Unit (AU) detection tasks using popular benchmarks for each; RAF-DB and BP4D. Our experiments show that CL-based methods, on average, outperform popular bias mitigation techniques, strengthening the need for further investigation into CL for the development of fairer FER algorithms., Comment: Accepted at the Workshop on Lifelong Learning and Personalization in Long-Term Human-Robot Interaction (LEAP-HRI) at the 16th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2021. arXiv admin note: substantial text overlap with arXiv:2103.08637

Published
2021

13. Domain-Incremental Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition

Author

Churamani, Nikhil, Kara, Ozgur, and Gunes, Hatice

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

As Facial Expression Recognition (FER) systems become integrated into our daily lives, these systems need to prioritise making fair decisions instead of aiming at higher individual accuracy scores. Ranging from surveillance systems to diagnosing mental and emotional health conditions of individuals, these systems need to balance the accuracy vs fairness trade-off to make decisions that do not unjustly discriminate against specific under-represented demographic groups. Identifying bias as a critical problem in facial analysis systems, different methods have been proposed that aim to mitigate bias both at data and algorithmic levels. In this work, we propose the novel usage of Continual Learning (CL), in particular, using Domain-Incremental Learning (Domain-IL) settings, as a potent bias mitigation method to enhance the fairness of FER systems while guarding against biases arising from skewed data distributions. We compare different non-CL-based and CL-based methods for their classification accuracy and fairness scores on expression recognition and Action Unit (AU) detection tasks using two popular benchmarks, the RAF-DB and BP4D datasets, respectively. Our experimental results show that CL-based methods, on average, outperform other popular bias mitigation techniques on both accuracy and fairness metrics.

Published
2021
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21. Assessment of the fetal thymic-thoracic ratio in pregnant women with intrahepatic cholestasis: a prospective case-control study.

Author

Agaoglu, Zahid, Tanacan, Atakan, Bozkurt Ozdal, Burcu, Basaran, Ezgi, Serbetci, Hakkı, Ozturk Agaoglu, Merve, Okutucu, Gulcan, Kara, Ozgur, and Sahin, Dilek

Subjects
MEDIASTINUM, RISK assessment, THYMUS, RECEIVER operating characteristic curves, NEONATAL intensive care units, BILE acids, FETAL ultrasonic imaging, PREGNANT women, TERTIARY care, NEONATAL intensive care, DESCRIPTIVE statistics, IMMUNE system, LONGITUDINAL method, HOSPITAL care of newborn infants, CASE-control method, STATISTICS, COMPARATIVE studies, CONFIDENCE intervals, INFLAMMATION, PREGNANCY complications, CHOLESTASIS, REGRESSION analysis, SENSITIVITY & specificity (Statistics), BLOOD, DISEASE risk factors, DISEASE complications, FETUS, PREGNANCY
Abstract

To examine the fetal thymic-thoracic ratio (TTR) in intrahepatic cholestasis of pregnancy (ICP). This prospective case-control study was conducted in a single tertiary center. The sample consisted of 86 pregnant women at 28–37 weeks of gestation, including 43 women with ICP and 43 healthy controls. TTR was calculated for each patient using the anterior-posterior measurements of the thymus and intrathoracic mediastinal measurements. The median TTR value was found to be smaller in the ICP group compared to the control group (0.32 vs. 0.36, p<0.001). The ICP group had a greater rate of admission to the neonatal intensive care unit (NICU) (p<0.001). Univariate regression analysis revealed that lower TTR values increased the possibility of NICU admission six times (95 % confidence interval: 0.26–0.39, p=0.01). A statistically significant negative correlation was detected between TTR and the NICU requirement (r: −0.435, p=0.004). As a result of the receiver operating characteristic analysis, in predicting NICU admission, the optimal cut-off value of TTR was determined to be 0.31 with 78 % sensitivity and 67 % specificity (area under the curve=0.819; p<0.001). We determined that the fetal TTR may be affected by the inflammatory process caused by the maternal-fetal immune system and increased serum bile acid levels in fetal organs in the presence of ICP. We consider that TTR can be used to predict adverse pregnancy outcomes in patients with ICP. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Prenatal diagnosis and postnatal outcomes of cavum septum pellucidum et vergae.

Author

Serbetci, Hakki, Tanacan, Atakan, Sahin, Refaettin, Ozkavak, Osman Onur, Haksever, Murat, Basarir, Mehmet Utku, Kara, Ozgur, and Sahin, Dilek

Subjects
INVASIVE diagnosis, FETAL abnormalities, MEDICAL screening, PRENATAL diagnosis, PREGNANCY outcomes, HYPOPLASTIC left heart syndrome
Abstract

Introduction: Evaluation of demographic characteristics and postnatal outcomes of fetuses with cavum septum pellucidum et vergae (CSPV) diagnosis followed in a tertiary center. Methods: This retrospective study was conducted in Ankara Bilkent City Hospital perinatology clinic between 2020-2023. Cases with the prenatal diagnosis of CSPV were evaluated. Demographic features, prenatal ultrasound findings, noninvasive screening test results, invasive diagnostic test results, prenatal anomaly screening ultrasound findings, and postnatal outcomes were reported. Results: There was a total of 24 prenatally diagnosed CSPV cases during the study period. The mean gestational week at diagnosis was 25.6 ± 3.2 weeks. Nineteen patients participated in noninvasive screening tests; five patients declined them. Noninvasive screening tests revealed low risk in 17 patients and high risk in 2. Amniocentesis was performed in 5 patients; 3 of them had a normal karyotype, 1 fetus was diagnosed with Smith-Lemli-Opitz syndrome, and 1 fetus had trisomy 21. Six patients with isolated CSPV were accepted and underwent fetal MRI, other eighteen patients refused MRI. MRI corrected the CSPV in all six patients, and they had no additional findings. Five (%21) fetuses were admitted to the intensive care unit because of recurrent absence convulsions (n=1), anal atresia (n=1), cleft lip palate (n=1), respiratory distress (n=1) and hypoplastic left heart syndrome (n=1). Conclusion: CSPV is considered a normal variant of cavum septum pellucidum and can be diagnosed during ultrasound screening for fetal anomalies; in isolated cases perinatal outcomes are favorable. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Development of a Nomogram for Fetal Evans Index

Author

Sakcak, Bedri, primary, Tanacan, Atakan, additional, Denizli, Ramazan, additional, Farisogullari, Nihat, additional, Özkavak, Osman Onur, additional, Aktaş, Sadık Orhun, additional, Uzuner, Petek, additional, Demirci, Harun, additional, Kara, Ozgur, additional, and Şahin, Dilek, additional

Published
2024
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25. The effect of maternal asthma on serum PAPP-A levels and first trimester aneuploidy screening test running.

Author

Koc, Bergen Laleli, Ergun, Gonca Turker, Kara, Ozgur, Tanacan, Atakan, Oluklu, Deniz, Aktas, Betul Akgun, Kaya, Ecem, and Sahin, Dilek

Subjects
ANEUPLOIDY, ASTHMATICS, ASTHMA, PREGNANT women, CHORIONIC gonadotropins
Abstract

Introductıon: PAPP-A (Pregnancy-associated plasma protein-A) is considered a pro-inflammatory marker and its serum levels are elevated in non-pregnant patients with asthma. In the current research, we aimed to investigate whether maternal serum PAPP-A levels, a biomarker for first-trimester aneuploidy screening, differ in pregnant women with asthma compared to healthy pregnant women. Methods: In the first step, maternal serum PAPP-A MoM values, used as the first-trimester fetal aneuploidy screening marker, were compared between pregnant women with asthma and a healthy pregnant group. In the second step, the groups compared whether PAPP-A and fβ-HCG ( free β human chorionic gonadotropin) levels were below or above the cut-off values for Trisomy 21 and compared them according to maternal age (<35; ≥35). Results: The median PAPP-A level was found to be 2.15 IU/L (0.41-9.91) in the asthma group and 2.54 IU/L (0.56-11.40) in the control group, and there was no difference between the groups (P=0.363). The median PAPP-A MoM value was 0.99 (0.15-3.28) in the asthma group and 1.07 (0.33-3.37) in the control group. This result did not show a statistically significant difference (P = 0.694). No statistically significant difference was shown between the groups below and above 35 age (P=0.456). Conclusion: Maternal serum PAPP-A levels in pregnant women with asthma do not vary compared to the healthy pregnant group without asthma. Based on the results of our study, the first-trimester fetal aneuploidy screening test is a reliable screening method for pregnant women with asthma. [ABSTRACT FROM AUTHOR]

Published
2024
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26. Do Maternal Heart Diseases Affect Fetal Cardiac Functions?

Author

Okutucu, Gulcan, Oluklu, Deniz, Gulen Yildiz, Esra, Bastemur, Ayse Gulcin, Tanacan, Atakan, Kara, Ozgur, and Şahin, Dilek

Subjects
FETAL diseases, HEART diseases, HEART diseases in women, PREGNANCY complications, NEONATAL intensive care units
Abstract

Objectives: To investigate whether fetal cardiac function is affected by underlying heart disease in pregnant women. Methods: A total of 100 pregnant women who were ≥34 gestational weeks were included in the study, 40 in the maternal heart disease (MHD) group diagnosed with heart disease and 60 in the control group. All cardiac diseases in pregnant women were diagnosed preconceptionally and categorized according to the New York Heart Association (NYHA) classification system. Fetal cardiac functions of study groups were evaluated by M‐mode, color tissue Doppler imaging (c‐TDI), and pulsed wave Doppler. Results: Tricuspid annular plane systolic excursion and myocardial performance index (MPI) values were significantly higher and isovolumetric relaxation time was prolonged in the MHD group. The MPI value was found higher in MHD group with NYHA Class II compared to those with NYHA Class I. No significant change in any of the fetal tricuspid annular peak velocity values measured by c‐TDI in the MHD group. There were no differences in fetal cardiac functions and perinatal outcomes between pregnant women with acquired and congenital heart diseases. Patients in NYHA Class II had lower birth weight, 1st and 5th minute APGAR scores, and higher neonatal intensive care unit admission rates. Conclusions: Underlying heart diseases in pregnant women can cause alterations in the systolic and diastolic function of the fetal heart. High fetal MPI values detected in cardiac patients may indicate that cardiac pathologies during pregnancy affect fetal cardiac globular myocardial function. Cardiac pathologies that progress with restricted physical activity may cause changes in fetal cardiac function and may be associated with adverse perinatal outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Amniyotik Sıvı Embolisi Olgusunun Başarılı Yönetimi.

Author

SENAY, ZUMRUT CALISKAN, TANACAN, ATAKAN, KARA, OZGUR, OZCAN, NAMIK NEBI, and SAHIN, DILEK

Abstract

Copyright of Jinekoloji-Obstetrik & Neonatoloji Tip Dergisi is the property of T.C. Saglik Bakanligi Ankara Sehir Hastanesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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36. Erken Başlangıçlı Fetal Büyüme Kısıtlamasını (FGR) Öngörmede İlk Trimester CRL (baş popo mesafesi) Ölçümünün NT (ense saydımlığı) Ölçümlerine Oranının Rolü

Author

SAHIN, REFAETTIN, TANACAN, ATAKAN, SERBETCI, HAKKI, OZKAVAK, OSMAN ONUR, HAKSEVER, MURAT, KARA, OZGUR, BASARIR, MEHMET UTKU, and ŞAHIN, DILEK

Abstract

Copyright of Jinekoloji-Obstetrik & Neonatoloji Tip Dergisi is the property of T.C. Saglik Bakanligi Ankara Sehir Hastanesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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37. The impact of gestational diabetes on the development of fetal frontal lobe: A case–control study from a tertiary center.

Author

Sahin, Refaettin, Tanacan, Atakan, Serbetci, Hakki, Agaoglu, Zahid, Haksever, Murat, Ozkavak, Osman Onur, Karagoz, Busra, Kara, Ozgur, and Sahin, Dilek

Abstract

Purpose: To determine the effects of gestational diabetes mellitus (GDM) on fetal frontal lobe development. Methods: This study was conducted prospectively between May 2023 and August 2023 in Ankara City Hospital perinatology clinic. Maternal age, maternal body mass index (BMI), gestational week (GW), biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL), estimated fetal weight (EFW), frontal antero‐posterior diameter (FAPD), occipito‐frontal diameter (OFD), FAPD/OFD ratio, and FAPD/HC ratio, were compared between GDM (n = 40) and low risk controls (n = 56). Results: The mean maternal age was found higher in the GDM group compared to control group (p = 0.002). Maternal BMI was significantly higher in the GDM group than the control group (p = 0.01). Abdominal circumference (AC) was significantly higher in the GDM group compared to control group (p = 0.04). EFW was significantly higher in the GDM group compared to control group (p = 0.04). FAPD/OFD ratio was found to be higher in the GDM group than in the control group (p = 0.001). Among GDM patients, no statistically significant difference was found in the ultrasound measurements between the groups receiving insulin treatment and those without treatment. According to the correlation analysis results a moderate, positive, and statistically significant correlation was present between FAPD/OFD and GDM. In perinatal outcomes, the rate of neonatal intensive care unit admission was significantly higher in the GDM group. Discussion: Fetal frontal lobe development seems to be affected by GDM. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Domain-Incremental Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition.

Author

Churamani, Nikhil, Kara, Ozgur, and Gunes, Hatice

Abstract

As Facial Expression Recognition (FER) systems become integrated into our daily lives, these systems need to prioritise making fair decisions instead of only aiming at higher individual accuracy scores. From surveillance systems, to monitoring the mental and emotional health of individuals, these systems need to balance the accuracy versus fairness trade-off to make decisions that do not unjustly discriminate against specific under-represented demographic groups. Identifying bias as a critical problem in facial analysis systems, different methods have been proposed that aim to mitigate bias both at data and algorithmic levels. In this work, we propose the novel use of Continual Learning (CL), in particular, using Domain-Incremental Learning (Domain-IL) settings, as a potent bias mitigation method to enhance the fairness of Facial Expression Recognition (FER) systems. We compare different non-CL-based and CL-based methods for their performance and fairness scores on expression recognition and Action Unit (AU) detection tasks using two popular benchmarks, the RAF-DB and BP4D datasets, respectively. Our experimental results show that CL-based methods, on average, outperform other popular bias mitigation techniques on both accuracy and fairness metrics. [ABSTRACT FROM AUTHOR]

Published
2023
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46. Evaluation of Maternal Anxiety and Depression Levels in Pregnancies with Fetal Anomalies.

Author

KOC, BERGEN LALELİ, ERSAK, DUYGU TUGRUL, ELMAS, BURAK, CAN, KAZIM CİHAN, KARA, OZGUR, and SAHİN, DİLEK

Subjects
FETAL abnormalities, DEPRESSION in women, STATE-Trait Anxiety Inventory, CONSCIOUSNESS raising, PREGNANT women, ABORTION, INTRUSION detection systems (Computer security)
Abstract

Copyright of Jinekoloji-Obstetrik & Neonatoloji Tip Dergisi is the property of T.C. Saglik Bakanligi Ankara Sehir Hastanesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2023
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47. Genetic Ethiology, Associated Anomalies in Fetal Aberrant Right Subclavian Artery: A Retrospective Cohort Study in a Tertiary Hospital.

Author

Sakcak, Bedri, Denizli, Ramazan, Farisogulları, Nihat, Agaoglu, Zahid, Kara, Ozgur, Tanacan, Atakan, and Sahin, Dilek

Subjects
SUBCLAVIAN artery, FETAL abnormalities, CONGENITAL heart disease, TRISOMY 18 syndrome, SINGLE nucleotide polymorphisms
Abstract

Introduction: This study aimed to determine the prevalence of chromosomal anomalies in fetuses with isolated and non-isolated aberrant right subclavian artery (ARSA) and to evaluate its association with other congenital anomalies. Methods: From 1 June 2021 to 1 June 2023, 47 ARSA cases were diagnosed by prenatal ultrasound in our hospital. The fetuses were divided into isolated ARSA group and non-isolated ARSA group. Among the 47 fetuses, 15 were characterized in the isolated group and 32 with combined other ultrasonic abnormalities in the non-isolated group. General information, ultrasound presentation, chromosomal findings, and birth and pregnancy outcomes were reviewed retrospectively. Results: In the non-isolated ARSA group, 17 cases (53,1%, 17/32) were associated with congenital heart defects, and 8 cases (25 %, 8/32) were associated with extracardiac abnormalities. Chromosome karyotype analysis was performed successfully with all 23 samples, and a total of 8 abnormalities (17 %, 8/47) were detected, including 7 cases of trisomy 21, and 1 case of trisomy 18. Single-nucleotide polymorphism array was performed in these 5 cases. Microdeletion was detected in four cases, but one of the arrays was reported normal. Using SNP-array and karyotype analysis in fetuses with ARSA, the total chromosomal anomaly detection rate was found 25.5 % (12/47). Conclusion: The most common malformation accompanying ARSA is cardiac abnormality. Isolated ARSA has a low risk of chromosomal abnormalities, so invasive chromosomal testing is not recommended. Non-isolated ARSA has a high incidence of chromosomal abnormalities, so early karyotyping should be recommended. [ABSTRACT FROM AUTHOR]

Published
2023
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48. A Retrospective Analysis of Cases of Non-Immune Hydrops Fetalis in A Tertiary Center.

Author

Agaoglu, Merve Ozturk, Tanacan, Atakan, Agaoglu, Zahid, Kara, Ozgur, and Sahin, Dilek

Subjects
HYDROPS fetalis, GESTATIONAL age, OVERALL survival, RETROSPECTIVE studies, SURVIVAL rate, EDEMA
Abstract

Introduction: Non-immune hydrops fetalis (NIHF) can occur at different gestational ages and with different etiologies. The aim of this study was to investigate the association of gestational age at diagnosis and a novel clinical scoring system with survival in NIHF cases Methods: This retrospective study was conducted between January 2020 and January 2023 in the perinatology clinic of a tertiary care center. Maternal characteristics, causes ofNIHF, and survival rate were analyzed. The hydrops score was calculated and compared for those less than and greater than 20 weeks. Results: Of 41 NIHF, etiology was determined in 76% (87% <20 weeks vs. 70% ≥20 weeks), including cardiovascular malformations (27%), cystic hygromas (17%), and chromosomal defects (12%). Cystic hygromas were more common before 20 weeks. Cardiac malformations were the most common cause after 20 weeks. There was a negative correlation between live birth and hydrops score. The overall survival was 7.3%. The most favorable overall survival is in NIHF cases associated with fetal arrhythmias and placental pathology for the second and third trimesters, respectively. Conclusion: Earlier gestational age at diagnosis and higher hydrops score are associated with lower survival rates in NIHF cases. Determining the cause, accompanying structural abnormalities, and the week NIHF is diagnosed will help predict prognosis and apply treatments earlier to improve care for these fetuses and newborns [ABSTRACT FROM AUTHOR]

Published
2023
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49. Impact of neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), systemic inflammation index (SII), systemic inflammation response index (SIR-I), and aspartate transaminase/platelet ratio (APRI) in predicting pregnancy outcomes of inflammatory bowel disease

Author

Beser, Dilek Menekse, Ozgurluk, Izzet, Oluklu, Deniz, Yildiz, Esra Gulen, Kara, Ozgur, Tanacan, Atakan, and Sahin, Dilek

Subjects
NEUTROPHIL lymphocyte ratio, SYSTEMIC inflammatory response syndrome, ASPARTATE aminotransferase, GESTATIONAL age, BIRTH weight
Abstract

Aim: We aimed to investigate the effect of systemic inflammation indices in predicting pregnancy outcomes of inflammatory bowel disease (IBD). Materials and Methods: Pregnant women with Crohn's disease (CD) and Ulcerative colitis (UC) were identified from hospital medical records. Demographic features, disease type, duration and activity, and obstetric outcomes such as gestational age, mode of delivery, birth weight, Apgar scores at the first and fifth minutes after birth, and neonatal intensive care unit admission were assessed. Laboratory tests were conducted in the first trimester, including complete blood count and liver function. Neutrophil/lymphocyte ratio (NLR), derived neutrophil/lymphocyte ratio (dNLR), systemic inflammation index (SII), systemic inflammation response index (SIR-I), and aspartate transaminase/platelet ratio (APRI) were measured. Results: The study involved 48 pregnant women, 26 diagnosed with UC and 22 with CD. At least one attack occurred in 31.3% of all patients during pregnancy. For predicting attacks during pregnancy, the optimal cutoff values of dNLR, NLR, SII, SIR-I, and APRI were 2.12 (86.7% sensitivity, 82.8% specificity), 2.89 (86.7% sensitivity, 81.8% specificity), 850.7 109/L (66.7% sensitivity, 63.6% specificity), 1.06 109/L (66.7% sensitivity, 72.7% specificity), 0.051 (80% sensitivity, 75.8% specificity), respectively. A cut-off value of 0.07 for APRI (71.4% sensitivity and 73.2% specificity) was calculated to predict low birth weight. Conclusion: NLR, dNLR, SII, SIR-I, and APRI might help predict attacks in pregnant women with IBD. In addition, APRI may be utilized to predict low birth weight in pregnant women with IBD. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Results of Routine Antenatal Screening for Cytomegalovirus at a Tertiary Center.

Author

ERSAK, Duygu TUGRUL, OZGURLUK, Izzet, BASTEMUR, Ayse Gulcin, YILDIZ, Esra GULEN, SINACI, Selcan, TURGUT, Ezgi, KARA, Ozgur, TANACAN, Atakan, and SAHIN, Dilek

Subjects
MEDICAL screening, IMMUNOGLOBULIN M, PREGNANT women, CYTOMEGALOVIRUSES, CYTOMEGALOVIRUS diseases
Abstract

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Published
2023
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