Medical Technologies National Conference (TIPTEKNO)
2023 Medical Technologies Congress (TIPTEKNO)
10-12 Nov. 2023
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Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
Medical Technologies Congress (TIPTEKNO), 2023
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Assessing Dyslexia with Machine Learning: A Pilot Study Utilizing Google ML Kit
Publication Year: 2023,Page(s):1 - 4
Cited by: Papers (1)
In this study, we explore the application of Google ML Kit, a machine learning development kit, for dyslexia detection in the Turkish language. We collected face-tracking data from two groups: 49 dyslexic children and 22 typically developing children. Using Google ML Kit and other machine learning algorithms based on eye-tracking data, we compared their performance in dyslexia detection. Our findi...Show More
Automated Segmentation of Gray and White Matter Regions in Brain MRI Images for Computer Aided Diagnosis of ADHD
Publication Year: 2023,Page(s):1 - 4
Attention deficit hyperactivity (ADHD) is a psychiatric disorder that affects millions of children and many times last into adulthood. There is no single test that can show whether a person has ADHD. The symptoms of ADHD vary from person to person. Therefore it is hard to diagnose ADHD contrary many physical illness. Our aim is to create methods to minimize human effort and increase accurate of di...Show More
Sleep Stages Classification via EEG Signals Using Quadratic Support Vector Machine (SVM) Algorithm
Publication Year: 2023,Page(s):1 - 4
Sleep stages classification plays a crucial role in diagnosing and understanding sleep disorders. With the increasing prevalence of sleep disorders, there is a growing need for automated methods to assist in sleep stage classification. In this study, we present a novel approach for sleep stages classification using EEG and machine learning models. Our method involves the extraction of EEG features...Show More
Differential Microwave Imaging of Cerebral Hemorrhage via DORT Method
Publication Year: 2023,Page(s):1 - 4
Bleeding in the brain tissues may cause fatal health conditions and continuous monitoring of the change in this blood accumulation becomes important in the first few hours after the incident. The continuous post-event monitoring aims to detect the variations in the size and the shape of the hemorrhage regions. To this end, the human head is illuminated by non-ionizing electromagnetic radiation, an...Show More
Measurement of the Correlation of the Education of Radiology Technicians and the Level of Sequence Knowledge in the Field of Magnetic Resonance Imaging
Melike Demir;Ceren Buse Othan;Gülçiçek Dere;M. Olcay Çizmeli;Ali Mertcan Köse
Publication Year: 2023,Page(s):1 - 4
The responsibility of the radiology technician in the Magnetic Resonance Imaging (MRI) unit is to take the relevant area of the patient upon request from the physician. At first, the technician selects the patient’s body region to be captured (usually over a human figure in anatomical posture) to start the acquisition on the MR monitor he uses. Acquisition options such as anatomical detail, how to...Show More
Classification of Human Emotions Based on Multivariate Spectral EEG Attributes and CNNs
Publication Year: 2023,Page(s):1 - 4
Human emotions are complex behavioral processes involving neural and chemical interactions in many layers of the human body. It plays a significant role in physical and mental health, in daily decisions, and in social communication. Investigating emotion is among the most popular areas of electroencephalogram (EEG) topics in the literature since physiological signals are hard to conceal and it pro...Show More
Machine Learning to Predict the Effect of Cold Atmospheric Plasma on the Surface Properties of Biomaterials
Yusra Dolunay Sula;Gizem Dilara Ozdemir;Mehmet Akif Ozdemir;Utku Kursat Ercan
Publication Year: 2023,Page(s):1 - 4
Cold atmospheric plasma (CAP) applications are widely used to find solutions to various problems in the biomedical field. Nowadays, CAP has become a preferred method to be used in many studies aimed at improving the surface properties of biomaterials. CAP applications, which are frequently used for surface modification of biomaterials, increase the surface roughness by etching without harming the ...Show More
Prediction of Antimicrobial Efficacy of Direct Cold Atmospheric Plasma Treatment via Ensemble Learning-based Regression Models
Elcin Erkal;Gizem Dilara Ozdemir;Mehmet Akif Ozdemir;Utku Kursat Ercan;Onan Guren
Publication Year: 2023,Page(s):1 - 4
Cold atmospheric plasma (CAP) has found successful applications in diverse fields like biological decontamination, altering surface properties, and medical treatments. Its notable effectiveness against microorganisms underscores its established utility. Nevertheless, challenges persist, exemplified by the difficulty in comparing results from different research laboratories due to variations in CAP...Show More
EEG Based Communication System by Using Artificial Neural Networks
Publication Year: 2023,Page(s):1 - 4
In this study, an EEG based eye-blink communication system has been developed for people with severe motor disabilities. This system uses the eye-blink signals of the person in order to analyze the information contained in these signals and vocalizes them. For this purpose, in the first step, EEG signals were obtained from the electrode placed on above of the left eye with the wireless NeuroSky Mi...Show More
GAN-generated Synthetic Data and SVM-based Feature Selection for Improved Cardiovascular Disease Prediction
Publication Year: 2023,Page(s):1 - 4
Early diagnosis requires cardiovascular disease forecasting. Past patient interests can improve machine learning predictions. This study uses a Generative Adversarial Network (GAN) to augment data to address the issue of insufficient datasets. Our objective is to use the GAN and feature selection (FS) to tackle the issue of class imbalance. The study assesses the efficacy of three different machin...Show More
Deep Learning and QR Code based Automated Diagnosis of Premature Retinopathy
Mustafa Yenice;Çağatay Berke Erdaş;Eşay Kiran Yenice;Caner Kara;İstemi Han ÇELİK;Dilek Ulubaş Işik
Publication Year: 2023,Page(s):1 - 4
Cited by: Papers (1)
Retinopathy of prematurity (ROP) is a condition that affects premature neonates and can cause blindness. Deep learning can assist ophthalmologists in diagnosing retinopathy of prematurity. Although medical images are needed for deep learning-based decision support systems, these images are difficult to obtain. As an alternative to medical images, patient examination information can also be used in...Show More
Noisy Label-Resistant Deep Learning Methods for Cancer Diagnosis in Histopathology Images
Publication Year: 2023,Page(s):1 - 4
Histopathology, one of the anatomical pathology tools, is one of the pathology branches specialising in the histological evaluation of diseased tissues. Histopathological images are examined by pathologists in the diagnosis of cancer and other diseases. Pathologists analyse the general tissue in detail in the diagnostic process, which requires a laborious workload and time. This study proposes a d...Show More
Frequency Response Analysis of a Surface Acoustic Wave Based Piezoelectric Mass Measurement Sensor
Publication Year: 2023,Page(s):1 - 4
Novel applications of surface acoustic waves (SAW) include sensing of biological agents in different media. A SAW sensor is excited by inter-digital-transducer (IDT), which has nested electrode legs, and different types of waves may propagate through the sensor depending on the selection of materials. Some of the computational analysis types are eigenvalue, and transient solutions. Both of them mi...Show More
Skin Cancer Diagnosis Using Deep Learning Techniques Feed by Dermoscopic Images
Publication Year: 2023,Page(s):1 - 4
Skin cancer is the uncontrolled growth of abnormal cells in the epidermis, the outermost layer of the skin. Types of skin cancer, one of the most common types of cancer in the world, are basal cell carcinoma, squamous cell carcinoma and melanoma. On the other hand, skin cancer types are generally examined in two groups as melanoma and non-melanoma, since melanoma causes a higher mortality rate due...Show More
Evaluation of Deep Learning Techniques in the Diagnosis of Polycystic Ovary Syndrome
Publication Year: 2023,Page(s):1 - 4
Polycystic ovary syndrome is an endocrine disorder that causes infertility. In addition, polycystic ovary syndrome increases the risk of type 2 diabetes, gestational diabetes, venous thromboembolism, cerebrovascular and cardiovascular disease, and endometrial cancer. The high prevalence of this disease and it’s associated with other health complications place an excessive burden on the health syst...Show More
Effect of the Anti-scatter Grid on the Detective Quantum Efficiency in Digital Mammography
Publication Year: 2023,Page(s):1 - 4
Detective quantum efficiency (DQE) is a frequency dependent measure of the efficiency of a digital detector in converting incident x-ray energy into an image signal. The anti-scatter grid’s effect on DQE for amorph selenium (a-Se) detector-based full-field digital mammography was examined in this study. DQE measurements were carried out with and without an anti-scatter grid as described in the IEC...Show More
Comparison of EEG- Based Deep Neural Network Classifiers for Emotion Recognition using Selected Electrodes
Publication Year: 2023,Page(s):1 - 4
In this study, SVM and DNN models were employed to classify participants’ emotional states using the publicly available SEED dataset, achieving impressive accuracy rates of 79.8% for DNN and 79.4% for SVM, surpassing the accuracies of previous models. Furthermore, our electrode reduction study, which optimized electrode placement by focusing on emotionally relevant brain regions, yielded high accu...Show More
Preliminary design of a wearable haptic finger and prototype production steps are presented in this study. Mechanical structural design is given with dimensions only. Proposed electrical part and sensor alternatives are also included. Printed partes are combined to get complete mechanism. This design will be planned to be used for finger rehabilitation purposes in further stages.Show More
Robotic Arm Control Using Machine Learning-Based EOG Signal Classifier
Ayse Nur Ay Gul;Muharrem Sahin;Tugba Kandis;Kadriye Kavrak;Zilan Oner
Publication Year: 2023,Page(s):1 - 4
Electrooculography (EOG) signals are a type of signal analyzed for detecting eye movements. In this project, features were extracted from EOG data collected from various subjects, and these features were then fed into machine learning algorithms k-Nearest Neighbor (KNN), Long-Short Term Memory (LSTM), Support Vector Machine (SVM), Decision Tree (DT)). The outputs of the algorithms were compared wi...Show More
Developing Eye Tracking Exercise System for Treatment of Lazy Eye
Kaan Kurtel;Melahat Kizil;Umuthan Ercan;Suzan E. Ozsimsek;Hasan Baris Mihci
Publication Year: 2023,Page(s):1 - 4
The aim of this study is to develop a fun and effective computer application game for children with amblyopia and to prevent eye strain in people whose work or lifestyle involves constantly looking at screens. The main motivation is to use children’s enthusiasm for playing video games for the treatment of amblyopia. For this, hardware and software products were brought together, and a software was...Show More
Investigation of Awareness and Consciousness of Technicians on Anesthesia Applications in Medical Imaging Examinations
Serkan Kara;Gülçiçek Dere;M. Olcay Çizmeli;Senem Polat;Ali Mertcan Köse;Rümeysa Kumcağız
Publication Year: 2023,Page(s):1 - 4
As minimally invasive techniques become more common in MRI units, the need for anesthesia support has increased. While recognizing and addressing the contraindications and concerns that may develop in a patient is similar to what is already done in the surgical setting, the additional requirements and limitations of the imaging environment and procedure require specific solutions. MRI units, as in...Show More
Detection of Attention Deficit Hyperactivity Disorder using Decision-level Fusion of Brain Connectivity Information Based on Deep Learning
Ozlem Karabiber Cura;Fatma Gunseli Ciklacandir;Aydin Akan;Sibel Kocaaslan Atli
Publication Year: 2023,Page(s):1 - 4
Attention Deficit Hyperactivity Disorder (ADHD) is a neurological disorder that often first appears in children. The condition is treated via behavioral studies, but there is no definitive technique to identify it. Electroencephalography (EEG) signals of ADHD patients are widely investigated to understand alterations in the brain. We offered EEG connectivity featured image creation to be used as i...Show More
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
Medical Technologies Congress (TIPTEKNO), 2023
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