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Search Results: 1 - 10 of 167540 matches for " E. Chatzimichail "
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Predicting Asthma Outcome Using Partial Least Square Regression and Artificial Neural Networks
E. Chatzimichail,E. Paraskakis,A. Rigas
Advances in Artificial Intelligence , 2013, DOI: 10.1155/2013/435321
Abstract:
Predicting Asthma Outcome Using Partial Least Square Regression and Artificial Neural Networks
E. Chatzimichail,E. Paraskakis,A. Rigas
Advances in Artificial Intelligence , 2013, DOI: 10.1155/2013/435321
Abstract: The long-term solution to the asthma epidemic is believed to be prevention and not treatment of the established disease. Most cases of asthma begin during the first years of life; thus the early determination of which young children will have asthma later in their life counts as an important priority. Artificial neural networks (ANN) have been already utilized in medicine in order to improve the performance of the clinical decision-making tools. In this study, a new computational intelligence technique for the prediction of persistent asthma in children is presented. By employing partial least square regression, 9 out of 48 prognostic factors correlated to the persistent asthma have been chosen. Multilayer perceptron and probabilistic neural networks topologies have been investigated in order to obtain the best prediction accuracy. Based on the results, it is shown that the proposed system is able to predict the asthma outcome with a success of 96.77%. The ANN, with which these high rates of reliability were obtained, will help the doctors to identify which of the young patients are at a high risk of asthma disease progression. Moreover, this may lead to better treatment opportunities and hopefully better disease outcomes in adulthood. 1. Introduction Artificial neural networks (ANNs) are one of the main constituents of the artificial intelligence (AI) techniques. Besides the different applications in many other areas, neural networks are also used in health and medicine areas, such as biomedical signal processing, diagnosis of diseases, and medical decision [1, 2]. ANNs have an excellent capability of learning the relationship between the input-output mapping from a given dataset without any prior knowledge or assumptions about the statistical distribution of the data [3]. This capability of learning from a certain dataset without any a priori knowledge makes the neural networks suitable for classification and prediction tasks in practical situations. Furthermore, neural networks are inherently nonlinear which makes them more practicable for accurate modeling of complex data patterns, in contrast to many traditional methods based on linear techniques. Due to their performance, they can be applied in a wide range of medical fields such as cardiology, gastroenterology, pulmonology, oncology, neurology, and pediatrics [1]. Several studies have proposed ANN models for the prediction of various diseases. The authors of [4] developed an ANN to determine whether patients had breast cancer or not. If they had, its type could be determined by using ANN and
γ-H2AX: A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer
E. Chatzimichail,D. Matthaios,D. Bouros,P. Karakitsos,K. Romanidis,S. Kakolyris,G. Papashinopoulos,A. Rigas
International Journal of Genomics , 2014, DOI: 10.1155/2014/160236
Abstract: Cancer is a leading cause of death worldwide and the prognostic evaluation of cancer patients is of great importance in medical care. The use of artificial neural networks in prediction problems is well established in human medical literature. The aim of the current study was to assess the prognostic value of a series of clinical and molecular variables with the addition of γ-H2AX—a new DNA damage response marker—for the prediction of prognosis in patients with early operable non-small cell lung cancer by comparing the γ-H2AX-based artificial network prediction model with the corresponding LR one. Two prognostic models of 96 patients with 27 input variables were constructed by using the parameter-increasing method in order to compare the predictive accuracy of neural network and logistic regression models. The quality of the models was evaluated by an independent validation data set of 11 patients. Neural networks outperformed logistic regression in predicting the patient’s outcome according to the experimental results. To assess the importance of the two factors p53 and γ-H2AX, models without these two variables were also constructed. JR and accuracy of these models were lower than those of the models using all input variables, suggesting that these biological markers are very important for optimal performance of the models. This study indicates that neural networks may represent a potentially more useful decision support tool than conventional statistical methods for predicting the outcome of patients with non-small cell lung cancer and that some molecular markers, such as γ-H2AX, enhance their predictive ability. 1. Introduction Prediction is one of the most interesting areas where intelligent systems are utilized [1]. In particular, prediction is an attempt to accurately forecast the evolution or outcome of a specific situation, using as input information a concrete set of variables that describe this situation [2]. In medicine, the valid and effective interpretation of medical data and the correct and early diagnosis along with a documented prognostic evaluation of the clinical and pathological data are very important parameters for a better management of the disease [3]. Prediction is a very difficult task because the expert human can hardly process the huge amount of data and usually suffers from absence of good and accurate analysis of these laboratory data [4, 5]. Lung cancer is the most common cause of cancer mortality worldwide for both men and women, causing approximately 1.2 million deaths per year. In the United States, there were 221.000
Optic nerve sonography in the diagnostic evaluation of adult brain injury
Theodoros Soldatos, Dimitrios Karakitsos, Katerina Chatzimichail, Matilda Papathanasiou, Athanasios Gouliamos, Andreas Karabinis
Critical Care , 2008, DOI: 10.1186/cc6897
Abstract: Seventy-six critical care patients (58 males; 47 ± 18 years old) were included in the study. Fifty patients suffered from brain injury, whereas 26 had no intracranial pathology and served as control individuals. Initially, brain-injured patients were evaluated clinically (Glasgow Coma Scale) and using a semiquantitative (I to VI) neuroimaging scale (Marshall Scale). Thereafter, the patients were divided into those with moderate (Marshall Scale = I and Glasgow Coma Scale > 8 [n = 18]) and severe (Marshall Scale = II to VI and Glasgow Coma Scale ≤8 [n = 32]) brain injury. All patients underwent noninvasive measurement of the ICP (estimated ICP) by transcranial Doppler sonography, and synchronous ONSD measurements by optic nerve sonography. Finally, invasive ICP measurement using an intraparenchymal catheter was performed in patients with severe brain injury.ONSD and estimated ICP were both significantly increased (6.1 ± 0.7 mm and 26.2 ± 8.7 mmHg, respectively; P < 0.0001) in patients with severe brain injury as compared with patients with moderate brain injury (4.2 ± 1.2 mm and 12.0 ± 3.6 mmHg) and compared with control individuals (3.6 ± 0.6 mm and 10.3 ± 3.1 mmHg). Furthermore, in patients with severe brain injury the ONSD measurements were strongly correlated with estimated ICP values (r = 0.80, P < 0.0001) as well as with the neuroimaging scale results (r = 0.82, P < 0.001). In the patients with severe brain injury, ONSD measurements correlated with invasive ICP values (r = 0.68, P = 0.002). The best cut-off value of ONSD for predicting elevated ICP was 5.7 mm (sensitivity = 74.1% and specificity = 100%).ONSD measurements correlate with noninvasive and invasive measurements of the ICP, and with head computed tomography scan findings in brain-injured adults. Hence, optic nerve sonography may serve as an additional diagnostic tool that could alert clinicians to the presence of elevated ICP, whenever invasive ICP evaluation is contraindicated and/or is not available
Frequency of genetic diseases and health coverage of children requiring admission in a general pediatric clinic of northern Greece
Theodoros Lialiaris, Elpis Mantadakis, Dimitra Kareli, Panagiotis Mpountoukas, Aggelos Tsalkidis, Athanassios Chatzimichail
Italian Journal of Pediatrics , 2010, DOI: 10.1186/1824-7288-36-9
Abstract: The causes of admission, as recorded in the medical records were categorized in terms of the major organ and/or system involved and/or the underlying pathology, with emphasis on diseases with a genetic background. Duplicate admissions, i.e., admissions of the same child for the same underlying disease were excluded. Additional information recorded was age, sex, and type of health insurance of all admitted children. Distribution of the causes of admission by study year was compared by chi-square. A p value < 0.05 was considered significant.Over the study period, there were 4,947 admissions in 2,818 boys and 2,129 girls. Respiratory diseases were the most common accounting for 30%, while infectious diseases followed with 26.4%. The frequency of chromosomal abnormalities among the hospitalized children was only 0.06%. However, if we consider diseases with an underlying genetic background, this percentage rises to 5%. Approximately 10.3% of the admitted children had no health insurance.The percentage of children hospitalized in our area due to a disease with an underlying genetic background was 5%. This percentage pertains to a Department of Pediatrics that has no inpatient subspecialty units and which is located within a General hospital, because hospitalizations for genetic diseases are more frequent in specialized pediatric hospitals, with competence in clinical genetics. The double figure of uninsured children is worrisome and dictates the need for governmental efforts for universal pediatric health coverage in our country.In the last 40 years, several studies investigated the frequency of genetic diseases in pediatric hospitals in developed countries [1-5]. However, to the best of our knowledge, such a study has never been done in Greece. The University General Hospital of Alexandroupolis is the teaching hospital of the Medical School of the Democritus University of Thrace. It is located in the area of Evros, Thrace, in Northern Greece, and has a well-organized and
Sonographic Lobe Localization of Alveolar-Interstitial Syndrome in the Critically Ill
Konstantinos Stefanidis,Stavros Dimopoulos,Chrysafoula Kolofousi,Demosthenes D. Cokkinos,Katerina Chatzimichail,Lewis A. Eisen,Mitchell Wachtel,Dimitrios Karakitsos,Serafim Nanas
Critical Care Research and Practice , 2012, DOI: 10.1155/2012/179719
Abstract: Introduction. Fast and accurate diagnosis of alveolar-interstitial syndrome is of major importance in the critically ill. We evaluated the utility of lung ultrasound (US) in detecting and localizing alveolar-interstitial syndrome in respective pulmonary lobes as compared to computed tomography scans (CT). Methods. One hundred and seven critically ill patients participated in the study. The presence of diffuse comet-tail artifacts was considered a sign of alveolar-interstitial syndrome. We designated lobar reflections along intercostal spaces and surface lines by means of sonoanatomy in an effort to accurately localize lung pathology. Each sonographic finding was thereafter grouped into the respective lobe. Results. From 107 patients, 77 were finally included in the analysis (42 males with mean age years, APACHE II score , and lung injury score ). US exhibited high sensitivity and specificity values (ranging from over 80% for the lower lung fields up to over 90% for the upper lung fields) and considerable consistency in the diagnosis and localization of alveolar-interstitial syndrome. Conclusions. US is a reliable, bedside method for accurate detection and localization of alveolar-interstitial syndrome in the critically ill. 1. Introduction Pulmonary diseases with involvement of the alveolar space and the interstitium (alveolar-interstitial syndrome) are common in the critically ill. Diagnostic assessment of the alveolar-interstitial syndrome includes chest radiography and computed tomography (CT). Chest CT is considered the “gold standard” test for the diagnosis of most pulmonary disorders in the intensive care unit (ICU). However, serial CT examinations may be required to followup the clinical course of pulmonary disorders and the results of therapy increasing radiation exposure. Also, this may be time consuming and hazardous as critically ill patients who oftentimes suffer from severe respiratory insufficiency are transferred to another unit. Historically, lung was considered a poorly accessible organ for ultrasound (US) assessment mainly due to abundance of air. However, in patients with lung disease extending to the pleura, US can be particularly useful for a wide range of applications [1, 2]. Recent studies have shown the significant role of lung US in detecting pulmonary diseases [3–15]. Areas of ground-glass adjacent to the pleura, areas of consolidation and areas of thickening of the interstitium can be easily detected using lung US [3–13]. The sonographic imaging of pulmonary diseases is based on the detection and quantification of
Electrical muscle stimulation preserves the muscle mass of critically ill patients: a randomized study
Vasiliki Gerovasili, Konstantinos Stefanidis, Konstantinos Vitzilaios, Eleftherios Karatzanos, Panagiotis Politis, Apostolos Koroneos, Aikaterini Chatzimichail, Christina Routsi, Charis Roussos, Serafim Nanas
Critical Care , 2009, DOI: 10.1186/cc8123
Abstract: Forty-nine critically ill patients (age: 59 ± 21 years) with an APACHE II admission score ≥13 were randomly assigned after stratification upon admission to receive daily EMS sessions of both lower extremities (EMS-group) or to the control group (control group). Muscle mass was evaluated with US, by measuring the cross sectional diameter (CSD) of the vastus intermedius and the rectus femoris of the quadriceps muscle.Twenty-six patients were finally evaluated. Right rectus femoris and right vastus intermedius CSD decreased in both groups (EMS group: from 1.42 ± 0.48 to 1.31 ± 0.45 cm, P = 0.001 control group: from 1.59 ± 0.53 to 1.37 ± 0.5 cm, P = 0.002; EMS group: from 0.91 ± 0.39 to 0.81 ± 0.38 cm, P = 0.001 control group: from 1.40 ± 0.64 to 1.11 ± 0.56 cm, P = 0.004, respectively). However, the CSD of the right rectus femoris decreased significantly less in the EMS group (-0.11 ± 0.06 cm, -8 ± 3.9%) as compared to the control group (-0.21 ± 0.10 cm, -13.9 ± 6.4%; P < 0.05) and the CSD of the right vastus intermedius decreased significantly less in the EMS group (-0.10 ± 0.05 cm, -12.5 ± 7.4%) as compared to the control group (-0.29 ± 0.28 cm, -21.5 ± 15.3%; P < 0.05).EMS is well tolerated and seems to preserve the muscle mass of critically ill patients. The potential use of EMS as a preventive and rehabilitation tool in ICU patients with polyneuromyopathy needs to be further investigated.clinicaltrials.gov: NCT00882830Critical illness polyneuromyopathy (CIPNM) is a common complication of critical illness presenting with muscle weakness, diminished tendon reflexes, difficult weaning from mechanical ventilation [1,2], and prolonged intensive care unit (ICU) and hospital stay [2,3], and is associated with increased mortality [4]. CIPNM is reported to have an incidence ranging from 25 to 50% [5,6] or higher [7] depending on the criteria used for diagnosis and the patient population evaluated. In afflicted patients muscle weakness may persist for months and a percentag
Human embryonal epithelial cells of the developing small intestinal crypts can express the Hodgkin-cell associated antigen Ki-1 (CD30) in spontaneous abortions during the first trimester of gestation
Demetrio Tamiolakis, John Venizelos, Maria Lambropoulou, Silva Nikolaidou, Sophia Bolioti, Maria Tsiapali, Dionysios Verettas, Panagiotis Tsikouras, Athanasios Chatzimichail, Nikolas Papadopoulos
Theoretical Biology and Medical Modelling , 2005, DOI: 10.1186/1742-4682-2-1
Abstract: We investigated the immunohistochemical expression of CD30 antigen in 15 paraffin-embedded tissue samples representing small intestines from fetuses after spontaneous abortion in the 8th, 10th and 12th weeks using the monoclonal antibody Ki-1. Hormones had been administered to all our pregnant women to support gestation. In addition, a panel of monoclonal antibodies was used to identify leukocytes (CD45/LCA), B-lymphocytes (CD20/L-26) and T-lymphocytes (CD3). Our findings were correlated with those obtained simultaneously from intestinal tissue samples obtained from 15 fetuses after therapeutic or voluntary abortions.The results showed that: (1) epithelial cells in the developing intestinal crypts express the CD30 (Ki-1) antigen; (2) CD30 expression in these epithelial cells is higher in cases of hormonal administration than in normal gestation. In the former cases (hormonal support of gestation) a mild mononuclear intraepithelial infiltrate composed of CD3 (T-marker)-positive cells accompanies the CD30-positive cells.CD30 antigen, a member of the tumor necrosis factor (TNF) receptor superfamily [1-3], was originally identified as a cell surface antigen on primary and cultured Hodgkin's and Reed-Sternberg cells by use of the monoclonal antibody Ki-1 [4,5]. CD30 antigen is normally expressed by a subset (15–20%) of CD3+ T cells after activation by various stimuli [6]. Its expression is stimulated by interleukin (IL)-4 during lineage commitment of na?ve human T cells [7,8] and is augmented by the presence of CD28 co-stimulatory signals [9]. CD30 also is expressed at variable levels in different non-Hodgkin's lymphomas (NHL) as well as in several virally transformed T and B cell lines [5,10]. In particular, CD30 is a specific marker of a subset of peripheral T cell NHLs known as anaplastic large cell lymphomas (ALCL) [5]. More recently, preferential CD30 expression has been detected on a subset of tissue and circulating CD4+ and CD8+ T cells producing mainly Th2 cytoki
Cluster Model of Formation of Subnuclear and Subatomic Objects  [PDF]
E. E. Lin
Journal of Modern Physics (JMP) , 2014, DOI: 10.4236/jmp.2014.53018
Abstract:

The paper describes the development results on one-dimensional (1D) asymptotic model of the formation kinetics for the objects (clusters) of subnuclear (quark) and subatomic (nuclear) matters. A concept of the objects distribution density wave φ(a, t) in space of sizes a lies in the basis for analytical description of the processes under consideration. The proposed formalism makes it possible to describe in an adequate way the final outcomes of the well-known catastrophic phenomena in the world of elementary particles. Mass characteristics of different processes of approach to equilibrium in nuclear reactions are calculated.

The Gene as Natural Nanomaterial for Treatment of Diseases  [PDF]
E. E. Escultura
Open Journal of Biophysics (OJBIPHY) , 2017, DOI: 10.4236/ojbiphy.2017.71003
Abstract: As an application of the grand unified theory (GUT) to medicine, this paper introduces two natural nanomaterials—the gene and electromagnetic wave. They are involved in the proposed treatment of genetic and infectious diseases. It introduces the superstring as the fundamental building block of matter and the basic constituent of dark matter, one of the two fundamental states of matter. It also introduces the primum, unit of visible or ordinary matter, the other fundamental state of matter. They are convertible to each other by the action of basic cosmic or electromagnetic waves. Eleven biological laws define biology as a biological and physical theory. The gene is the primitive ingredient of living things and, therefore, the beginning of biological life and the virus the simplest living thing. Treatment ranges from genetic modification and alteration to remove undesirable symptom through genetic sterilization to stop the spread of the disease and outright destruction of the disease. Genetic sterilization and outright destruction apply also to infectious diseases. The paper concludes with a blueprint for research and development of appropriate technologies for the treatment.
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