Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299287
Hande UĞraŞ, G. Özdemir, Utku Kürşat Ercan
Wounds can be vital dangerous for a patient’s life, so wound healing is one of the essential topics. Tissue engineers have investigated tissue scaffolds for wound healing. Scaffolding materials can be natural or synthetic, and the researchers use polycaprolactone (PCL) and zinc oxide (ZnO) nanoparticles to improve wound healing and minimize the infection risk. Cold atmospheric plasma (CAP) is a new area. CAP is used in many areas such as cancer treatment; besides, it is the more crucial properties to avoid the bacteria formation and provide healing the many different types of wound tissues. In this sense, plasma is of great importance in protecting life in all kinds of materials that will be placed inside the living thing. In this study, PCL were used in different amounts of ZnO-NPs; 5%, 10%, and 15% of total weight. Then, scaffolds were obtained using the electrospinning technique. CAP applied on the obtained scaffolds in different exposure times; 15 sec., 25sec., and 35sec. After CAP treatment; contact angle measurement and antibacterial test were made. Test results show that, depending on the CAP exposure time, the contact angle decreases, but the antibacterial effect increases.
{"title":"Investigation of Cold Atmospheric Plasma Activity in PCL/ZnO Tissue Scaffolding To Be Used in Wound Tissues","authors":"Hande UĞraŞ, G. Özdemir, Utku Kürşat Ercan","doi":"10.1109/TIPTEKNO50054.2020.9299287","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299287","url":null,"abstract":"Wounds can be vital dangerous for a patient’s life, so wound healing is one of the essential topics. Tissue engineers have investigated tissue scaffolds for wound healing. Scaffolding materials can be natural or synthetic, and the researchers use polycaprolactone (PCL) and zinc oxide (ZnO) nanoparticles to improve wound healing and minimize the infection risk. Cold atmospheric plasma (CAP) is a new area. CAP is used in many areas such as cancer treatment; besides, it is the more crucial properties to avoid the bacteria formation and provide healing the many different types of wound tissues. In this sense, plasma is of great importance in protecting life in all kinds of materials that will be placed inside the living thing. In this study, PCL were used in different amounts of ZnO-NPs; 5%, 10%, and 15% of total weight. Then, scaffolds were obtained using the electrospinning technique. CAP applied on the obtained scaffolds in different exposure times; 15 sec., 25sec., and 35sec. After CAP treatment; contact angle measurement and antibacterial test were made. Test results show that, depending on the CAP exposure time, the contact angle decreases, but the antibacterial effect increases.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130062104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299309
A. Kavsaoğlu, ve Burak Bi̇lece, Besimcan Altiyaprak, ve Furkan Böyükçolak
There are people who have a lost limb or have no innate limb. In this study, it is aimed to create a data processing environment to improve the working performance of the prostheses to be developed for people with hand loss. Basically, Leap Motion and EMG devices were used. Simultaneous recording of data obtained with EMG and Leap Motion is provided using Arduino microcontroller and C # Interface design. In addition, a bionic hand control is provided from finger movements obtained with Leap Motion.
{"title":"C# Interface Design for Real-Time Signal Recording Oriented of Bionic Hand Control with Leap Motion and EMG Devices","authors":"A. Kavsaoğlu, ve Burak Bi̇lece, Besimcan Altiyaprak, ve Furkan Böyükçolak","doi":"10.1109/TIPTEKNO50054.2020.9299309","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299309","url":null,"abstract":"There are people who have a lost limb or have no innate limb. In this study, it is aimed to create a data processing environment to improve the working performance of the prostheses to be developed for people with hand loss. Basically, Leap Motion and EMG devices were used. Simultaneous recording of data obtained with EMG and Leap Motion is provided using Arduino microcontroller and C # Interface design. In addition, a bionic hand control is provided from finger movements obtained with Leap Motion.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"436 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123198974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299322
Iraz Çinar, İrem Aksoy, Günnur Güler
Investigation of the protein-drug active substance interactions has great importance in the fields of medicine, chemistry, pharmaceutical, biomedical and toxicology. In this study, binding properties of a potential anti-cancer drug agent ifosfamide with bovine serum albumin (BSA), one of the main ligand transporters in blood plasma, was analyzed by using ultraviolet and visible light (UV-Vis) spectroscopy along with molecular docking studies. The UV-Vis spectra of the constant BSA solution (20x $10^{-6}$ M) in complexes with various concentrations of ifosfamide (20x $10^{-6}$ M to 140x $10^{-6}$ M) were obtained at physiological pH. Besides, the BSA protein was docked with ifosfamide drug active substance via computational molecular docking method. Amino acids in the binding sites of the BSA protein and the binding distances of these amino acids to the ligand (ifosfamide), their scores and RMSD values were determined, revealing that the interaction is a spontaneous process. Both molecular docking and the spectral results demonstrated that the anti-cancer drug agent binds to BSA via non-covalent interactions, resulting in minute conformational changes in BSA.
{"title":"Spectroscopic and Computational Molecular Docking studies on the protein-drug interactions","authors":"Iraz Çinar, İrem Aksoy, Günnur Güler","doi":"10.1109/TIPTEKNO50054.2020.9299322","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299322","url":null,"abstract":"Investigation of the protein-drug active substance interactions has great importance in the fields of medicine, chemistry, pharmaceutical, biomedical and toxicology. In this study, binding properties of a potential anti-cancer drug agent ifosfamide with bovine serum albumin (BSA), one of the main ligand transporters in blood plasma, was analyzed by using ultraviolet and visible light (UV-Vis) spectroscopy along with molecular docking studies. The UV-Vis spectra of the constant BSA solution (20x $10^{-6}$ M) in complexes with various concentrations of ifosfamide (20x $10^{-6}$ M to 140x $10^{-6}$ M) were obtained at physiological pH. Besides, the BSA protein was docked with ifosfamide drug active substance via computational molecular docking method. Amino acids in the binding sites of the BSA protein and the binding distances of these amino acids to the ligand (ifosfamide), their scores and RMSD values were determined, revealing that the interaction is a spontaneous process. Both molecular docking and the spectral results demonstrated that the anti-cancer drug agent binds to BSA via non-covalent interactions, resulting in minute conformational changes in BSA.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127097538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299266
Fatma Muberra Yener, A. B. Oktay
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first broke out in Wuhan, China and COVID-19 disease spread throughout the world by its highly contagious nature. High death numbers have caused a massive panic across the globe. Fast and early diagnosis is the key for preventing the virus from spreading. Besides PCR test, computed tomography (CT) of lungs is also used for diagnosis of COVID-19. Since the amount of testing kits for the diagnosis is insufficient and the conventional diagnosis methods are slow, developing AI-based fast diagnosis tools is not only an alternative way but also an urgent requirement for such alarming situations as those people faced with today. In this study, we employed three popular CNN models, VGG16, VGG19, and Xception, to classify CT scans of suspected patient cases as COVID-19 infected and non-COVID-19. VGG16 achieved 93% accuracy with the best parameters on the test set.
{"title":"Diagnosis of COVID-19 with a Deep Learning Approach on Chest CT Slices","authors":"Fatma Muberra Yener, A. B. Oktay","doi":"10.1109/TIPTEKNO50054.2020.9299266","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299266","url":null,"abstract":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first broke out in Wuhan, China and COVID-19 disease spread throughout the world by its highly contagious nature. High death numbers have caused a massive panic across the globe. Fast and early diagnosis is the key for preventing the virus from spreading. Besides PCR test, computed tomography (CT) of lungs is also used for diagnosis of COVID-19. Since the amount of testing kits for the diagnosis is insufficient and the conventional diagnosis methods are slow, developing AI-based fast diagnosis tools is not only an alternative way but also an urgent requirement for such alarming situations as those people faced with today. In this study, we employed three popular CNN models, VGG16, VGG19, and Xception, to classify CT scans of suspected patient cases as COVID-19 infected and non-COVID-19. VGG16 achieved 93% accuracy with the best parameters on the test set.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127741321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299297
Nadide Gülşah Gülenç, M. Kartal
Many devices have been developed in order to increase the life standards of the medical device industry with the development of wireless communication technology today. Real- time monitoring of medical data and to inform users in case of emergencies has been indispensable. In this study, it was aimed to measure respiration, heart rate, SpO2 and body temperature of babies simultaneously with the wireless communication system. Thanks to this system we have designed, it will be an important convenience for the correct diagnosis to be easily monitored by the healthcare professional of the data of babies who need to be under surveillance in the home environment despite the end of their treatment in the hospital. Thanks to this implemented system, the follower can easily follow the baby’s status with the mobile application and receive alerts in sudden situations.
{"title":"Noninvasive Measurement of Baby’s Vital Datas and Mobile Monitoring - Analysis System Design","authors":"Nadide Gülşah Gülenç, M. Kartal","doi":"10.1109/TIPTEKNO50054.2020.9299297","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299297","url":null,"abstract":"Many devices have been developed in order to increase the life standards of the medical device industry with the development of wireless communication technology today. Real- time monitoring of medical data and to inform users in case of emergencies has been indispensable. In this study, it was aimed to measure respiration, heart rate, SpO2 and body temperature of babies simultaneously with the wireless communication system. Thanks to this system we have designed, it will be an important convenience for the correct diagnosis to be easily monitored by the healthcare professional of the data of babies who need to be under surveillance in the home environment despite the end of their treatment in the hospital. Thanks to this implemented system, the follower can easily follow the baby’s status with the mobile application and receive alerts in sudden situations.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121355165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299314
Hayriye Aktaş Dinçer, D. Gökçay
Conventional MRI studies have reported several structural changes such as brain atrophy and ventricular enlargement in healthy aging. Quantitative MRI (qMRI) allows the measurement of tissue characteristics such as the longitudinal relaxation times (T1) which provides unique and complementary information to widely used measures of brain signal characteristics. In this study, the T1 values on entire brain were mapped with an ROI based method. T1 prolongation with aging was demonstrated on numerous cortical and subcortical areas such as caudate, thalamus and prefrontal cortex. This outcome was interpreted as increased demyelination in these structures.
{"title":"Prolongation of Longitudinal Relaxometry Characteristics in Healthy Aging: a Whole Brain MRI Study","authors":"Hayriye Aktaş Dinçer, D. Gökçay","doi":"10.1109/TIPTEKNO50054.2020.9299314","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299314","url":null,"abstract":"Conventional MRI studies have reported several structural changes such as brain atrophy and ventricular enlargement in healthy aging. Quantitative MRI (qMRI) allows the measurement of tissue characteristics such as the longitudinal relaxation times (T1) which provides unique and complementary information to widely used measures of brain signal characteristics. In this study, the T1 values on entire brain were mapped with an ROI based method. T1 prolongation with aging was demonstrated on numerous cortical and subcortical areas such as caudate, thalamus and prefrontal cortex. This outcome was interpreted as increased demyelination in these structures.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115563269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299254
Abbas Memiş, Songül Varlı, F. Bilgili
This paper introduces a study of automatic femoral head detection in magnetic resonance imaging (MRI) data sequences. For the 3D detection of the multiform femoral heads having both spheric and aspheric shape structures, the threedimensional form of the Integro-differential Operator (IDO) was performed. Following a set of image pre-processing operations including image intensity normalization, histogram equalization, morphological correction, hip joint separation and image binarization performed on bilateral hip MRI data sequences, the hip joints images are obtained in binary form in 3D. Then, the 3D form of IDO is performed in a predefined image volume to detect the femoral heads. Within the experimental studies performed on 8 bilateral hip MRI data sequences belonging to 6 LeggCalve-Perthes disease (LCPD) patients, promising success rates were observed. In detection of a total of 16 femoral heads, 8 of which are spheric and 8 of which are aspheric, 0.7021 (± 0.3160) and 0.6757 (± 0.2989) DSC values measured for the spheric and aspheric femoral heads, respectively.
{"title":"3D Femoral Head Detection in MRI Data Sequences with the Integro-differential Operator","authors":"Abbas Memiş, Songül Varlı, F. Bilgili","doi":"10.1109/TIPTEKNO50054.2020.9299254","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299254","url":null,"abstract":"This paper introduces a study of automatic femoral head detection in magnetic resonance imaging (MRI) data sequences. For the 3D detection of the multiform femoral heads having both spheric and aspheric shape structures, the threedimensional form of the Integro-differential Operator (IDO) was performed. Following a set of image pre-processing operations including image intensity normalization, histogram equalization, morphological correction, hip joint separation and image binarization performed on bilateral hip MRI data sequences, the hip joints images are obtained in binary form in 3D. Then, the 3D form of IDO is performed in a predefined image volume to detect the femoral heads. Within the experimental studies performed on 8 bilateral hip MRI data sequences belonging to 6 LeggCalve-Perthes disease (LCPD) patients, promising success rates were observed. In detection of a total of 16 femoral heads, 8 of which are spheric and 8 of which are aspheric, 0.7021 (± 0.3160) and 0.6757 (± 0.2989) DSC values measured for the spheric and aspheric femoral heads, respectively.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114910871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299292
T. Aydemir, ve Mehmet Şahi̇n, Önder Aydemir
Hypertension is the condition where the normal blood pressure is high. This situation is manifested by the high pressure of the blood in the vein towards the vessel wall. Hypertension mostly affects the brain, kidneys, eyes, arteries and heart. Therefore, the diagnosis of this common disease is important. It may take days, weeks or even months for diagnosis. Often a device called a blood pressure holter is connected to the person for 24 or 48 hours and the person’s blood pressure is recorded at certain intervals. Diagnosis can be made by the specialist physician considering these results. In recent years, various physiological measurement techniques have been used to accelerate this time-consuming diagnostic phase and propose intelligent models. One of these techniques is photopletesmography (PPG). In this study, a model for the detection of hypertension disease in individuals using the optimal frequency ranges of 2.1 second short-time PPG signals was proposed. The proposed model was tested with PPG data of 219 people and the disease was determined with classification accuracy of 76.15%. The results showed that the diagnosis of hypertension based on machine learning can be performed effectively by using frequency ranges of 1.4-5.7 Hz of short time PPG signals.
{"title":"Determination of Hypertension Disease with Optimal Frequency Range of Short-Time Photopletismography Signals","authors":"T. Aydemir, ve Mehmet Şahi̇n, Önder Aydemir","doi":"10.1109/TIPTEKNO50054.2020.9299292","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299292","url":null,"abstract":"Hypertension is the condition where the normal blood pressure is high. This situation is manifested by the high pressure of the blood in the vein towards the vessel wall. Hypertension mostly affects the brain, kidneys, eyes, arteries and heart. Therefore, the diagnosis of this common disease is important. It may take days, weeks or even months for diagnosis. Often a device called a blood pressure holter is connected to the person for 24 or 48 hours and the person’s blood pressure is recorded at certain intervals. Diagnosis can be made by the specialist physician considering these results. In recent years, various physiological measurement techniques have been used to accelerate this time-consuming diagnostic phase and propose intelligent models. One of these techniques is photopletesmography (PPG). In this study, a model for the detection of hypertension disease in individuals using the optimal frequency ranges of 2.1 second short-time PPG signals was proposed. The proposed model was tested with PPG data of 219 people and the disease was determined with classification accuracy of 76.15%. The results showed that the diagnosis of hypertension based on machine learning can be performed effectively by using frequency ranges of 1.4-5.7 Hz of short time PPG signals.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128321261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299218
Emel Bakay, N. Topaloglu
The healing effect of light at low power and energy density can be used as a treatment or alternative supportive method in various diseases. The photobiostimulation effect created on neural cells is also a very promising approach in the treatment of important neurodegenerative diseases such as Alzheimer’s disease. In this study, the response of PC12 cells to photobiomodulation was investigated as a result of the low level laser therapy with 655 nm diode laser after triple treatment. The red light at an energy density of 1, 3 and 5 J/cm2 was applied to PC12 cells three times with 24h intervals. The differentiation capacity of the cells and the elongation rates of neurites were assessed. The neurite lengths were calculated by analyzing the microscopic images of the cells. Neurite-forming capacity and differentiation rate of PC12 cells was at the maximum level after the application with 1 J/cm2 energy, nearly 2 times of the control group. 5 J/cm2 of energy density strongly inhibited the cell proliferation and the elongation of the neurites. The cell viability percentages of the cells showed that 5 J/cm2 energy density inhibited cell viability with a rate of nearly 30%. The outcomes of this study emphasized that the adjustment of light parameters in photobiomodulation applications may result in biostimulation or bioinhibition depending on the intensity and the irradiance levels applied on the cells.
{"title":"Photobiomodulation with 655-nm Laser Light to Induce the Differentiation of PC12 Cells","authors":"Emel Bakay, N. Topaloglu","doi":"10.1109/TIPTEKNO50054.2020.9299218","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299218","url":null,"abstract":"The healing effect of light at low power and energy density can be used as a treatment or alternative supportive method in various diseases. The photobiostimulation effect created on neural cells is also a very promising approach in the treatment of important neurodegenerative diseases such as Alzheimer’s disease. In this study, the response of PC12 cells to photobiomodulation was investigated as a result of the low level laser therapy with 655 nm diode laser after triple treatment. The red light at an energy density of 1, 3 and 5 J/cm2 was applied to PC12 cells three times with 24h intervals. The differentiation capacity of the cells and the elongation rates of neurites were assessed. The neurite lengths were calculated by analyzing the microscopic images of the cells. Neurite-forming capacity and differentiation rate of PC12 cells was at the maximum level after the application with 1 J/cm2 energy, nearly 2 times of the control group. 5 J/cm2 of energy density strongly inhibited the cell proliferation and the elongation of the neurites. The cell viability percentages of the cells showed that 5 J/cm2 energy density inhibited cell viability with a rate of nearly 30%. The outcomes of this study emphasized that the adjustment of light parameters in photobiomodulation applications may result in biostimulation or bioinhibition depending on the intensity and the irradiance levels applied on the cells.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"36 173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125923063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-19DOI: 10.1109/TIPTEKNO50054.2020.9299286
Emrah Irmak
The novel coronavirus, generally known as COVID19, is a new type of coronavirus which first appeared in Wuhan Province of China in December 2019. The biggest impact of this new coronavirus is its very high contagious feature which brings the life to a halt. As soon as data about the nature of this dangerous virus are collected, the research on the diagnosis of COVID-19 has started to gain a lot of momentum. Today, the gold standard for COVID-19 disease diagnosis is typically based on swabs from the nose and throat, which is time-consuming and prone to manual errors. The sensitivity of these tests are not high enough for early detection. These disadvantages show how essential it is to perform a fully automated framework for COVID-19 disease diagnosis based on deep learning methods using widely available X-ray protocols. In this paper, a novel, powerful and robust Convolutional Neural Network (CNN) model is designed and proposed for the detection of COVID-19 disease using publicly available datasets. This model is used to decide whether a given chest X-ray image of a patient has COVID-19 or not with an accuracy of 99.20%. Experimental results on clinical datasets show the effectiveness of the proposed model. It is believed that study proposed in this research paper can be used in practice to help the physicians for diagnosing the COVID-19 disease.
{"title":"A Novel Deep Convolutional Neural Network Model for COVID-19 Disease Detection","authors":"Emrah Irmak","doi":"10.1109/TIPTEKNO50054.2020.9299286","DOIUrl":"https://doi.org/10.1109/TIPTEKNO50054.2020.9299286","url":null,"abstract":"The novel coronavirus, generally known as COVID19, is a new type of coronavirus which first appeared in Wuhan Province of China in December 2019. The biggest impact of this new coronavirus is its very high contagious feature which brings the life to a halt. As soon as data about the nature of this dangerous virus are collected, the research on the diagnosis of COVID-19 has started to gain a lot of momentum. Today, the gold standard for COVID-19 disease diagnosis is typically based on swabs from the nose and throat, which is time-consuming and prone to manual errors. The sensitivity of these tests are not high enough for early detection. These disadvantages show how essential it is to perform a fully automated framework for COVID-19 disease diagnosis based on deep learning methods using widely available X-ray protocols. In this paper, a novel, powerful and robust Convolutional Neural Network (CNN) model is designed and proposed for the detection of COVID-19 disease using publicly available datasets. This model is used to decide whether a given chest X-ray image of a patient has COVID-19 or not with an accuracy of 99.20%. Experimental results on clinical datasets show the effectiveness of the proposed model. It is believed that study proposed in this research paper can be used in practice to help the physicians for diagnosing the COVID-19 disease.","PeriodicalId":426945,"journal":{"name":"2020 Medical Technologies Congress (TIPTEKNO)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122134890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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