Browsing by Author "Kocoglu, Arif"

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City Hospitals Model in Biomedical Calibration Service
(2015) Kocak, Onur; Budak, Erdem I.; Beytar, Faruk; Ozgode, Busra; Coruh, Baris; Kocoglu, Arif; Erogul, Osman
Clinical engineering comprise of management of medical technology, medical device maintenance, repair, and calibration which they are bought according to capacity of health institution. In this study, entirely using principles have been given about medical device maintenance, repair, and calibration. A model has been designed which is biomedical calibration production service to new vast city hospitals. The hospitals have high bed capacity and because of that there are more different types of medical devices in their inventory. According to the model has been depicted about separating medical devices too. Besides, process planning has been materialized in biomedical calibration. A new work flow model has been suggested result of evaluating both of calibration and preventive maintenance. Moreover in this study mentioned about laboratory accreditation to international traceability need. Furthermore an offset investment model has been examined to medical device calibrators which they will have bought city hospitals. Urgent actions have detected for all consider authority to the investment model success.
A Clinical Engineering Approach for Design and Management of Central Sterilization Units
(2015) Kocak, Onur; Ozgode, Busra; Kocoglu, Arif; Erogul, Osman; 0000-0002-4640-6570; 0000-0003-4803-5504; AAW-3005-2021; AAF-8122-2020
Central Sterilization Unit (CSU) are the units that performs sterilization of medical devices, instruments and consumables which used in hospitals and these units are planned to provide services within a quality management system and traceability. The numbers of sterilization procedures are carried out in medium and large scale hospitals, this situation can lead to reduced efficiency of the sterilization process have become critical. In this study, using a medium scale hospital as base, planning to work in coordination with the clinical engineering unit the structure of a central sterilization unit that coordinated to work with clinical engineering unit is recommended. The following issues are discussed in detail: architecture of the CSU, departments, staff, process of monitoring, validation and quality cycles. In addition, contributions to the technical efficiency of the sterilization process from biomedical engineers and technicians which are appointed by the clinical engineering units were examined.
Deep Learning Based Multi Modal Approach for Pathological Sounds Classification
(2020) Ankishan, Haydar; Kocoglu, Arif
Automatic detection of voice disorders is very important because it makes the diagnosis process simpler, cheaper and less time consuming. In the literature, there are many studies available on the analysis of voice disorders based on the characteristics of the voice and subdividing the result of this analysis. In general, these studies have been carried out in order to subdivide the sound into pathological - normally sub - groups by means of certain classifiers as a result of subtraction of the features on frequency, time or hybrid axis. In contrast to existing approaches, in this study, a multiple- deep learning model using feature level fusion is proposed to distinguish pathological-normal sounds from each other. First, a feature vector (HOV) on the hybrid axis was obtained from the raw sound data. Then two CNN models were used. The first model has used raw audio data and the second model has used HOV as an input. Feature data in both model SoftMax layers were obtained as a matrix, and canonical correlation analysis (Canonical Correlation Analysis (CCA) was applied at feature level fusion. The new obtained feature vector was used as an input for multiple support vector machines (M-SVMs), Decision Tree (DTC) and naive bayes (NBC) classifiers. When the experimental results are examined, it is seen that the new multi-model based deep learning architecture provides superior success in classifying pathological sound data. With the results of the study, it will be possible to automatically detect and classify the pathology of these patients according to the proposed system.
A Medical Waste Management Model for Public Private Partnership Hospitals
(2015) Kocak, Onur; Kurtuldu, Huseyin; Akpek, Ali; Kocoglu, Arif; Erogul, Osman; JMC-5224-2023
Today, with developing technologies and expanding health care system, medical waste has reached a fairly large volume. Particularly, the extensive use of disposable medical devices and supplies are among the factors that increase the production of medical waste. Monitoring the processes involving the separation, temporary storage, disposal, and transfer of medical waste is critical in terms of the environment and human health. In this study, the implementation of medical waste collection, separation and classification processes were surveyed in new city hospitals constructed with public-private partnership. The standards for temporarily holding wastes were also discussed. Furthermore, the cost analysis required for the handling and disposal of medical waste was provided. By means of studying the medical waste disposal methods, few suggestions regarding the most appropriate methods and models of offset technology investments for the city hospitals were proposed.