A deep learning feature extraction-based hybrid approach for detecting pediatric pneumonia in chest X-ray images.

Pneumonia is a disease caused by bacteria, viruses, and fungi that settle in the alveolar sacs of the lungs and can lead to serious health complications in humans. Early detection of pneumonia is necessary for early treatment to manage and cure the disease. Recently, machine learning-based pneumonia detection methods have focused on pneumonia in adults. Machine learning relies on manual feature engineering, whereas deep learning can automatically detect and extract features from data. This study proposes a deep learning feature extraction-based hybrid approach that combines deep learning and machine learning to detect pediatric pneumonia, which is difficult to standardize. The proposed hybrid approach enhances the accuracy of detecting pediatric pneumonia and simplifies the approach by eliminating the requirement for advanced feature extraction. The experiments indicate that the hybrid approach using a Medium Neural Network based on AlexNet feature extraction achieved a 97.9% accuracy rate and 98.0% sensitivity rate. The results show that the proposed approach achieved higher accuracy rates than state-of-the-art approaches.

Noninvasive Hemoglobin Measurement Reduce Invasive Procedures in Thalassemia Patients.

This study was conducted to investigate the agreement between laboratory hemoglobin (LabHb) measured in venous blood and noninvasive, spectrophotometric hemoglobin (SpHb) measurement and the usability of SpHb measurement in the transfusion decision-making in patients with thalassemia whose hemoglobin (Hb) was monitored by taking blood samples at frequent intervals and who were transfused. Cardiac pulse, oxygen saturation, Pleth variability index (PVI), and SpHb values were measured in patients who came to the hematology outpatient clinic for a control visit and whose Hb levels were planned to be measured. Venous blood samples were taken for LabHb measurement, which we accept as the gold standard. Cohen's kappa value was calculated for the agreement between SpHb measurements and LabHb values. The relationship and predictability between both measurement methods were evaluated by Pearson correlation analysis, a modified Bland-Altman plot and the linear regression model. In the study conducted with a total of 110 children with thalassemia, a moderate level of agreement between the two measurement methods (kappa = 0.370, p < 0.0001) and a significantly high correlation between the two tests (r = 0.675) were found. The mean bias between the differences was found to be 0.3 g/dL (-1.27 to 1.86 g/dL). The sensitivity and the specificity of SpHb in identifying patients who needed transfusions (Hb <10.0 g/dL) were calculated as 92.2 and 57.1%, respectively. Our results suggest SpHb measurement may be used to screen anemia in hemodynamically stable hemoglobinopathy patients and even for transfusion decision-making with combination clinical findings.

Association of mindfulness and impulsivity with obesity

Abstract Background: The prevalence of obesity has more than doubled over the past three decades. Impulsivity is a multidimensional personality trait that potentially contributes to the development and maintenance of obesity. Mindful awareness can potentially minimize the automatic and inattentive reactions around food. Objectives: In our study, we aimed to research the relationship between impulsivity and mindful attention. Methods: The study population consisted of 60 outpatients aged 18 and older, with a body mass index (BMI) of at least 30 kg/m2 presenting to the psychiatry clinics of a secondary health care facility. The participants completed the Barratt Impulsiveness Scale (BIS), and the Mindful Attention Awareness Scale (MAAS). Results: The average age of participants was 39 years, BMI was 35.70 ± 4.54 kg/m2. BMI was not statistically significantly correlated with any of the scales, and the MAAS total score was negatively correlated with the impulsiveness scores, except for the motor impulsiveness subscale score. Dispositional mindfulness was negatively associated with impulsiveness scores, except for motor impulsiveness. Discussion: This study showed that there was a negative relationship between impulsivity and mindfulness. Therefore, using mindfulness techniques may decrease impulsivity, and may be extremely helpful in promoting better eating behaviors and weight regulation.

The Effects of Occupational Therapy and Psychosocial Interventions on Interpersonal Functioning and Personal and Social Performance Levels of Corresponding Patients.

INTRODUCTION: In this study, we aimed to investigate the effects of occupational therapy and psychosocial interventions on the interpersonal functioning and individual and social performance levels of corresponding patients under the heading of psychosocial treatment approaches in psychiatry clinics as well as the attitudes of the patients in regard to those interventions. METHODS: In 2013, out of psychotic (schizophrenia, bipolar disorder/mania) and nonpsychotic (depression, obsessive compulsive disorder, alcohol dependence) inpatients in our clinic, 48 patients who participated in occupational activities were included in the study group and 43 patients who did not participate in these activities were included in the control group. We prepared and implemented a 3-item questionnaire constructed by our team, which probed the patients' thoughts on these occupational activities. The Interpersonal Functioning Scale (IFS) and Personal and Social Performance Scale (PSP) were applied to both groups on hospital admission and discharge; variations in scale scores were evaluated on par with sociodemographic variables, and the study and control groups were compared. RESULTS: In total, 91% of the study group provided positive feedback regarding the aforementioned interventions. When comparing the study and control groups, the IFS variance score of the study group did not show a significant difference with respect to that of the control group. A statistically significant difference (p<0.0001) was observed in the PSP scores. Evaluation of the PSP of the occupational activities, focusing on sociodemographics and diagnostic labels, revealed a significant improvement in nonpsychotic patients (p=0.002) compared with psychotic patients, in females (p=0.001) compared with males, in unemployed patients (p=0.0001) compared with employed patients, in single patients (p=0.002) compared with married patients, in less-educated patients (p=0.004) compared with high school graduates, and in patients younger than 45 years (p=0.002) compared with those older than 45 years. CONCLUSION: The findings of our study showed coherence with the literature regarding similar studies conducted on psychotic subgroups. The results demonstrated significantly positive repercussions, specifically in the treatment of nonpsychotic patients; both groups benefited from occupational activities, as shown by improvements in all psychiatric inpatients' PSP scores in comparison with scores of the control group. We concluded that the recruitment of psychosocial treatment approaches enhanced personal and social performance in the patient groups, thereby leading to additional clinical benefits.

Non-contact estimation of heart rate and oxygen saturation using ambient light.

We propose a robust method for automated computation of heart rate (HR) from digital color video recordings of the human face. In order to extract photoplethysmographic signals, two orthogonal vectors of RGB color space are used. We used a dual tree complex wavelet transform based denoising algorithm to reduce artifacts (e.g. artificial lighting, movement, etc.). Most of the previous work on skin color based HR estimation performed experiments with healthy volunteers and focused to solve motion artifacts. In addition to healthy volunteers we performed experiments with child patients in pediatric intensive care units. In order to investigate the possible factors that affect the non-contact HR monitoring in a clinical environment, we studied the relation between hemoglobin levels and HR estimation errors. Low hemoglobin causes underestimation of HR. Nevertheless, we conclude that our method can provide acceptable accuracy to estimate mean HR of patients in a clinical environment, where the measurements can be performed remotely. In addition to mean heart rate estimation, we performed experiments to estimate oxygen saturation. We observed strong correlations between our SpO2 estimations and the commercial oximeter readings.

Intravital confocal and two-photon imaging of dual-color cells and extracellular matrix mimics.

We report our efforts in identifying optimal scanning laser microscope parameters to study cells in three-dimensional culture. For this purpose we studied contrast of extracellular matrix (ECM) mimics, as well as signal attenuation, and bleaching of red and green fluorescent protein labeled cells. Confocal backscattering, second harmonic generation (SHG), and autofluorescence were sources of contrast in ECM mimics. All common ECM mimics exhibit contrast observable with confocal reflectance microscopy. SHG imaging on collagen I based hydrogels provides high contrast and good optical penetration depth. Agarose is a useful embedding medium because it allows for large optical penetration and exhibits minimal autofluorescence. We labeled breast cancer cells' outline with DsRed2 and nucleus with enhanced green fluorescent protein (eGFP). We observed significant difference both for the bleaching rates of eGFP and DsRed2 where bleaching is strongest during two-photon excitation (TPE) and smallest during confocal imaging. But for eGFP the bleaching rate difference is smaller than for DsRed2. After a few hundred microns depth in a collagen I hydrogel, TPE fluorescence of DsRed2 becomes twice as strong compared to confocal imaging. In fibrin and agarose gels, the imaging depth will need to be beyond 1 mm to notice a TPE advantage.

Dual tree complex wavelet transform based denoising of optical microscopy images.

Photon shot noise is the main noise source of optical microscopy images and can be modeled by a Poisson process. Several discrete wavelet transform based methods have been proposed in the literature for denoising images corrupted by Poisson noise. However, the discrete wavelet transform (DWT) has disadvantages such as shift variance, aliasing, and lack of directional selectivity. To overcome these problems, a dual tree complex wavelet transform is used in our proposed denoising algorithm. Our denoising algorithm is based on the assumption that for the Poisson noise case threshold values for wavelet coefficients can be estimated from the approximation coefficients. Our proposed method was compared with one of the state of the art denoising algorithms. Better results were obtained by using the proposed algorithm in terms of image quality metrics. Furthermore, the contrast enhancement effect of the proposed method on collagen fiber images is examined. Our method allows fast and efficient enhancement of images obtained under low light intensity conditions.