A Survey on Automated Diagnosis of Alzheimer's Disease Using Optical Coherence Tomography and Angiography

Retinal optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) are promising tools for the (early) diagnosis of Alzheimer's disease (AD). These non-invasive imaging techniques are cost-effective and more accessible than alternative neuroimaging tools. However, interpreting and classifying multi-slice scans produced by OCT devices is time-consuming and challenging even for trained practitioners. There are surveys on machine learning and deep learning approaches concerning the automated analysis of OCT scans for various diseases such as glaucoma. However, the current literature lacks an extensive survey on the diagnosis of Alzheimer's disease or cognitive impairment using OCT or OCTA. This has motivated us to do a comprehensive survey aimed at machine/deep learning scientists or practitioners who require an introduction to the problem. The paper contains 1) an introduction to the medical background of Alzheimer's Disease and Cognitive Impairment and their diagnosis using OCT and OCTA imaging modalities, 2) a review of various technical proposals for the problem and the sub-problems from an automated analysis perspective, 3) a systematic review of the recent deep learning studies and available OCT/OCTA datasets directly aimed at the diagnosis of Alzheimer's Disease and Cognitive Impairment. For the latter, we used Publish or Perish Software to search for the relevant studies from various sources such as Scopus, PubMed, and Web of Science. We followed the PRISMA approach to screen an initial pool of 3073 references and determined ten relevant studies (N=10, out of 3073) that directly targeted AD diagnosis. We identified the lack of open OCT/OCTA datasets (about Alzheimer's disease) as the main issue that is impeding the progress in the field.Comment: Submitted to Computerized Medical Imaging and Graphics. Concept, methodology, invest, data curation, and writing org.draft by Yasemin Turkan. Concept, method, writing review editing, and supervision by F. Boray Te

Efficient memory management algorithm for client-server database management systems

Due to the recent improvements in the price/performance characteristics of workstations and the networking capabilities, the client-server system architecture has become a target for database systems. A client-server database management system (DBMS) provides the management of a database that resides on a client-server system. Data-access requests of the clients are handled by the database servers. The whole database is stored on the disks that can be accessed by only the servers, and in order to reduce disk accesses, copies of database items can be cached in the global memory which comprises the memories of all the computers connected to the system. Designing efficient global memory management algorithms helps the transactions experience less disk input/output (I/O) during their execution. In this paper, we propose a global memory management algorithm for client-server DBMSs which aims to reduce disk I/O by increasing the portion of the database available in global memory. Performance of the algorithm is examined by a comparison with some previously proposed algorithms, using a simulation model designed for studying various performance issues in client-server DBMSs. Conditions for which the new algorithm provides significant improvements in the overall throughput of the system are identified

Using adaptive locally connected layer in attention based deep neural network for speech command recognition

Sesli komut tanıma insan-makine ara yüzüyle ilişkili aktif bir araştırma konusudur. Dikkat tabanlı derin ağlar ile bu tür problemler başarılı bir şekilde çözülebilmektedir. Bu çalışmada, var olan bir dikkat tabanlı derin ağ yöntemi, uyarlanır yerel bağlı (odaklanan) katman kullanılarak daha da geliştirilmiştir. Orijinal yönteminde sınandığı Google ve Kaggle sesli komut veri setlerinde karşılaştırmalı olarak yapılan deneylerde önerdiğimiz uyarlanır yerel bağlı katman kullanan dikkat tabanlı ağın tanıma doğruluğunu %2.6 oranında iyileştirdiği gözlemledik.Speech command recognition is an active research topic associated with the human-machine interface. Such problems can be successfully solved with attention-based deep networks. In this study, we improved one of the existing attentionbased deep network methods by using an adaptive locally connected (focused) layer. In the experiments we used Google and Kaggle datasets, which were also used in the reference. We observed that the recognition results can be improved significantly (2.6%) by the attention based deep network which uses adaptive locally connected layers.Publisher's Versio

Relationship Between The Levels of Growth Hormone, Leptin, Amylin, Glucagon Like Peptide-1 and Insulin Resistance in Obese Patients

Objective: The aim of this study is to determine the relationship between the levels of growth hormone, leptin, amylin, glucagon like peptide-1 and insulin resistance in obese patients

AKUT ATAK DÖNEMİNDEKİ KRONİK OBSTRÜKTİF AKCİĞER HASTALIĞI OLGUSUNUN KOLCABA’NIN KONFOR KURAMINA GÖRE İNCELENMESİ

Dispneyi rahat nefes alamamak olarak tanımlayan KOAH’lı hastalar, günlük yaşam aktivitelerini özgürce gerçekleştiremedikleri için konfor kaybından yakınmaktadırlar. Özellikle akut atak dönemlerinde artan dispnenin etkili yönetimi sağlanabilirse konfor düzeyide yükseltilebilir. Bu çalışmada konfor kuramı çerçevesinde akut atak dönemindeki KOAH olgusunun şiddetli dispne nedeniyle ile yaşadığı konfor sorunlarına ilişkin hemşirelik yönetimi ele alınmış ve kuramın kullanımına yönelik bir örnek oluşturulması amaçlanmıştır

Reference Intervals for Serum Immunoglobulin (IGA, IGG, IGM) and IGG Subclasses in Healthy Subjects

Aim: Regional reference values of immunoglobulin and immunoglobulin subgroups are necessary for clinical research and diagnosis. A main problem in determining the reference intervals, reference values show variability depending on laboratory and technical conditions against interregional and reference populations. In clinical laboratories mainly test kit's reference intervals are used according to the manufacturer. In this study it is aimed to determine reference interval values of regional immunoglobulin and IgG subgroups

Association of ischemia-modified albumin with oxidative stress status and insulin resistance in obese patients

Objectives: Obesity is associated with oxidative stress due to the overproduction of free radicals in some accompanying states, such as hyperglycemia, elevated lipid levels and chronic inflammation. Free radical accumulation may modify the structure of human serum albumin, generating ischemia-modified albumin (IMA), and increased serum levels of IMA have been linked to obesity-related diseases and oxidative damage. The association of IMA levels with oxidative stress and insulin resistance (IR) has not been evaluated in the context of obesity. The aim of this study is to determine IMA levels in the context of obesity and their relationship with oxidative status and insulin resistance. Methods: Sixty-one adult obese cases with body mass index (BMI) ≥ 30 were evaluated, with 30 healthy adults with 18.5 ≤ BMI ≤ 24.9 included in the control group. IMA, total antioxidant status (TAS), total oxidant status (TOS), oxidative stress index (OSI), total cholesterol, triglycerides, HDL and LDL-cholesterols were determined. Results: IMA, TAS, TOS, OSI, total cholesterol and LDL-cholesterol levels were not different between the control and obese groups (P-value >0.05), while triglyceride levels were determined to be higher and HDL-cholesterol levels were determined to be lower in the obese group (P-value 0.05), but the fasting blood glucose level was determined to be higher in the obese/IR(+) group than in the control group. Conclusions: We concluded that obesity and insulin resistance had no effect on IMA levels in the obese group, who showed no impairment in their oxidative balanc

Association of ischemia-modified albumin with oxidative stress status and insulin resistance in obese patients

Objectives: Obesity is associated with oxidative stress due to the overproduction of free radicals in some accompanying states, such as hyperglycemia, elevated lipid levels and chronic inflammation. Free radical accumulation may modify the structure of human serum albumin, generating ischemia-modified albumin (IMA), and increased serum levels of IMA have been linked to obesity-related diseases and oxidative damage. The association of IMA levels with oxidative stress and insulin resistance (IR) has not been evaluated in the context of obesity. The aim of this study is to determine IMA levels in the context of obesity and their relationship with oxidative status and insulin resistance. Methods: Sixty-one adult obese cases with body mass index (BMI) ≥ 30 were evaluated, with 30 healthy adults with 18.5 ≤ BMI ≤ 24.9 included in the control group. IMA, total antioxidant status (TAS), total oxidant status (TOS), oxidative stress index (OSI), total cholesterol, triglycerides, HDL and LDL-cholesterols were determined. Results: IMA, TAS, TOS, OSI, total cholesterol and LDL-cholesterol levels were not different between the control and obese groups (P-value >0.05), while triglyceride levels were determined to be higher and HDL-cholesterol levels were determined to be lower in the obese group (P-value <0.05). When IMA, TAS, TOS, OSI levels were compared between the control/IR(-), obese/IR(+) and obese/IR(-) groups, no statistically significant differences were detected (P-value >0.05), but the fasting blood glucose level was determined to be higher in the obese/IR(+) group than in the control group. Conclusions: We concluded that obesity and insulin resistance had no effect on IMA levels in the obese group, who showed no impairment in their oxidative balanc