Electroencephalographic Changes in Pregnant Women with Hyperemesis Gravidarum: A Case-Control Study.

Objective: Electroencephalogram (EEG), which is frequently used in the clinical practice of neurology, has also been investigated in eating disorders and some cortical dysfunctions have been reported. Based on this, we aimed to investigate EEG changes in pregnant women with hyperemesis gravidarum (HEG).

Materials And Methods: This case-control study was conducted on 66 pregnant women who applied to the Umraniye Training and Research Hospital, Department of Obstetrics and Gynecology.

The effects of hypercortisolism on the frequency and magnitude of sleep EEG waves in patients with Cushing syndrome: A spectral analysis study.

Objectives: Our aim was to investigate the effects of endogenous chronic hypercortisolism on sleep electroencephalogram (EEG) and differences between the adrenocorticotropic hormone (ACTH)-dependent and independent Cushing Syndrome (CS) patients through a sleep spectral analysis program.

Methods: A total of 32 patients diagnosed as having endogenous CS (12 ACTH-dependent and 20 ACTH-independent) and a control group comprising 16 healthy individuals were included in the study. Polysomnographic analysis was performed.

SERS-based sensor with a machine learning based effective feature extraction technique for fast detection of colistin-resistant Klebsiella pneumoniae.

Colistin-resistant Klebsiella pneumoniae (ColR-Kp) causes high mortality rates since colistin is used as the last-line antibiotic against multi-drug resistant Gram-negative bacteria. To reduce infections and mortality rates caused by ColR-Kp fast and reliable detection techniques are vital. In this study, we used a label-free surface-enhanced Raman scattering (SERS)-based sensor with machine learning algorithms to discriminate colistin-resistant and susceptible strains of K.

Drug-resistant Staphylococcus aureus bacteria detection by combining surface-enhanced Raman spectroscopy (SERS) and deep learning techniques.

Over the past year, the world's attention has focused on combating COVID-19 disease, but the other threat waiting at the door-antimicrobial resistance should not be forgotten. Although making the diagnosis rapidly and accurately is crucial in preventing antibiotic resistance development, bacterial identification techniques include some challenging processes. To address this challenge, we proposed a deep neural network (DNN) that can discriminate antibiotic-resistant bacteria using surface-enhanced Raman spectroscopy (SERS).

Identification of methicillin-resistant bacteria using surface-enhanced Raman spectroscopy and machine learning techniques.

To combat antibiotic resistance, it is extremely important to select the right antibiotic by performing rapid diagnosis of pathogens. Traditional techniques require complicated sample preparation and time-consuming processes which are not suitable for rapid diagnosis. To address this problem, we used surface-enhanced Raman spectroscopy combined with machine learning techniques for rapid identification of methicillin-resistant and methicillin-sensitive Gram-positive Staphylococcus aureus strains and Gram-negative Legionella pneumophila (control group).

The correlation between the electroencephalographic spectral analysis and salivary cortisol rhythm in insomnia.

Objective: Insomnia is a common sleep disorder that affects many adults either transiently or chronically. This study aimed to establish whether there is a relationship between the electroencephalographic (EEG) spectral analysis and salivary cortisol levels in insomnia and compared to healthy controls.

Materials And Methods: This case-control study included 15 insomnia patients and 15 healthy control subjects.

Evaluation of Two Types of Drug Treatment with QEEG in Children with ADHD.

Aims: The aim of this study is to evalute the effects of methylphenidate and atomoxetine treatments on electroencephalography (EEG) signals in volunteer children diagnosed with Attention Deficit and Hyperactivity Disorder(ADHD).

Methods: The study contained 40 children all of whom were between the ages of 7 and 17. The participants were classified into two groups as ADHD (n=20), which was in itself divided into two groups as ADHD-MPH (ADHD- Metylphenidate treatment) (n=10) and as ADHD-ATX (ADHD-Atomoxetin treatment) (n=10), and one control group (n=20).

Investigation of attention deficit hyperactivity disorder (ADHD) sub-types in children via EEG frequency domain analysis.

Aim Of The Study: To investigate the frequency domain effects and changes in electroencephalography (EEG) signals in children diagnosed with attention deficit hyperactivity disorder (ADHD).

Patients And Methods: The study contains 40 children. All children were between the ages of 7 and 12 years.

Effect of chewing on dental patients with total denture: an experimental study.

In this study, we have explored the prospect of assessing and following level of total denture adaptation by use of EMG signals recorded during gum chewing. Total of 14 edentulous patients, 6 women and 8 men, with an average age of 63±9 years, were recruited. Separate EMG recordings were obtained from left and right temporalis and masseter muscles of the patients for a period of 10 seconds, while they were chewing a sugar-free gum on their left and right sides.

Denoising of arterial and venous Doppler signals using discrete wavelet transform: effect on clinical parameters.

In this paper, the effects of a wavelet transform based denoising strategy on clinical Doppler parameters are analyzed. The study scheme included: (a) Acquisition of arterial and venous Doppler signals by sampling the audio output of an ultrasound scanner from 20 healthy volunteers, (b) Noise reduction via decomposition of the signals through discrete wavelet transform, (c) Spectral analysis of noisy and noise-free signals with short time Fourier transform, (d) Curve fitting to spectrograms, (e) Calculation of clinical Doppler parameters, (f) Statistical comparison of parameters obtained from noisy and noise-free signals. The decomposition level was selected as the highest level at which the maximum power spectral density and its corresponding frequency were preserved.

Investigation of the arterial stiffness on renal artery Doppler sonograms.

This study aims to identify the effect of stiffness on renal artery Doppler sonograms by using a curve fitting approach. The study includes 20 patients with suspected renovascular hypertension. Each patient underwent recordings during renal artery examinations before and after administration of Captopril 25 mg (Kapril tablet, MN Pharmaceuticals, Istanbul, Turkey).

A classification system for stenosis from mitral valve Doppler signals using adaptive network based fuzzy inference system.

In this study, cardiac Doppler parameters were studied in 60 patients with mitral valve stenosis and compared with 41 ages and sex matched healthy controls. Firstly, the sonograms which represent the changes in Doppler frequency with respect to time were performed from mitral valve Doppler signals using short time Fourier transformation (STFT) method. Secondly, the envelopes of these sonograms and data set depicted from sonogram envelopes were acquired.

Analysis of the electrogastrogram using discrete wavelet transform and statistical methods to detect gastric dysrhythmia.

Electrogastrography (EGG) is a method of recording stomach electrical activity from cutaneous electrodes placed on the abdominal surface. Compared with other electrophysiological measurements, such as electrocardiography, the progress of the applicability of the EGG has been very slow. Unlike imaging or manometrical studies, stomach motility disorders are not diagnosed based only on abnormal EGG parameters.

A high-voltage pulse generation instrument for electrochemotherapy method.

Electrochemotherapy (ECT) is a new method that uses anticancer drugs delivery with intensive electrical pulses. Recently, ECT as the treatment method can be applied for basal cell and spin cell carcinoma and for melanoma metastases. In this paper, a new design of a high voltage pulse generator with variable output pulse magnitude, repetition frequency, and pulse duration is presented.

A programmable iontophoretic instrument and its application for local anesthesia before surgery in urology.

In this paper, for an alternative anesthesia before transurethral resection of bladder tumors (TUR-BT) an original equipment which is used iontophoresis method was implemented. The implemented instrument is used on five patients for TUR-BT operations. This equipment can be programmable between 0 and 15 mA current by 1 mA steps and with in time 0 - 59 min.