Ανίχνευση κρίσεων επιληψίας σε δεδομένα ηλεκτροεγκεφαλογράφου

Βασικός τομέας ενασχόλησης της παρούσας διπλωματικής εργασίας είναι η ανίχνευση επιληπτικών κρίσεων με χρήση μεθόδων μηχανικής μάθησης. Τα δεδομένα που χρησιμοποιήθηκαν προέρχονται από επιφανειακά ηλεκτροεγκεφαλογραφήματα (EEG). Πρόκειται για τη CHB-MIT βάση δεδομένων που διατίθεται δωρεάν στην πλατφόρμα PhysioNet. Στα πλαίσια της υλοποίησης εξετάστηκε όλη η διαδικασία διαχείρισης των δεδομένων από τη λήψη τους, την εξαγωγή χαρακτηριστικών (μέση τιμή, διακύμανση, ασυμμετρία, κύρτωση, τυπική απόκλιση, διάμεσος, διασχίσεις μηδενικού άξονα, ενεργός τιμή, εύρος μεταβολής, εντροπία δείγματος, ισχύς μέσω PSD στις συχνότητες δέλτα, θήτα (theta), άλφα (alpha), βήτα (beta), γάμμα (gamma), μέγιστη αλληλοσυσχέτιση) σε αυτά, την κανονικοποίησή τους (z-score), τη μείωση διαστάσεων (PCA) με διατήρηση τής εγγενούς πληροφορίας τους, την εξισορρόπηση των δειγμάτων (Cluster Centroids, ADASYN), επιληπτικών και μη, έως την εκπαίδευση, τη βελτιστοποίηση (αναζήτηση πλέγματος) και την εφαρμογή των ταξινομητών (SVM, kNN, Απλοϊκός Bayes, Δέντρα Απόφασης, Τυχαίο Δάσος, LDA, Λογιστική Παλινδρόμηση, Νευρωνικό Δίκτυο με LSTM), την αξιολόγηση τους (ακρίβεια, ευαισθησία, ειδικότητα, αξιοπιστία, βαθμολογία F1, συντελεστής συσχέτισης Matthews, συντελεστής κ του Cohen) και τη σύγκριση των αποτελεσμάτων. Διενεργούνται τρία διαφορετικά πειράματα είτε χρησιμοποιώντας τις μετρήσεις από όλα τα ηλεκτρόδια είτε τμήμα αυτών. Η βασική διαφορά της μεθόδου μας σε σχέση με τη βιβλιογραφία είναι ότι εξετάζονται τα αποτελέσματα της γενίκευσης σε αντίθεση με τις εστιασμένες στον κάθε ασθενή μεθόδους που συνήθως συναντάται. Η υλοποίηση όλων των παραπάνω γίνεται μέσω της γλώσσας Python, που είναι η δημοφιλέστερη για εφαρμογές μηχανικής μάθησης, και της πλατφόρμας Jupyter.The main field of work of this thesis is the detection of seizures using machine learning methods. The data we used came from scalp electroencephalograms (EEGs). This is the CHB-MIT database, which is available for free, from the PhysioNet platform. In the context of the implementation, the whole process of data management was examined from their download, the extraction of characteristics (mean, variance, skewness, kurtosis, standard deviation, median, zero crossings, root mean square, peak to peak, sample entropy, power via PSD in the delta, theta, alpha, beta, gamma frequencies, maximum correlation) from them, their normalization (z-score), the reduction of dimensions (PCA) by preserving their inherent information, the balancing of epileptic and non-epileptic samples (Cluster Centroids, ADASYN) to training, optimization (grid search) and classifier implementation (SVM, kNN, Naive Bayes, Decision Trees, Random Forest, LDA, Logistic Regression, Neural Network with LSTM), their evaluation (accuracy, sensitivity/recall, specificity, precision, F1 score, Matthews correlation coefficient, Cohen's Kappa coefficient) and comparison of results. Three different experiments are performed either by using the measurements of all the electrodes or part of them. The main difference of our method in relation to the bibliography is that the results of the generalization of the methods are examined in contrast to the focused ones on each patient that is usually encountered. All of the above is done using Python, which is the most popular of machine learning applications, and the Jupyter platform

Παράλληλη Επιτάχυνση αλγορίθμων Dictionary Learning και Παραγοντοποίησης με εφαρμογή σε fMRI: k-SVD, αλγόριθμος MM, PARAFAC2

Η αξιοσημείωτη πρόοδος που παρατηρείται στην Ιατρική με την πάροδο των χρόνων σχετίζεται άμεσα με την ταχεία και ευρεία εξάπλωση της χρήσης των υπολογιστών στις επιστήμες υγείας (Ιατρική, Βιολογία, Βιοτεχνολογία). Οι πολύπλοκοι υπολογισμοί που απαιτούνται σε ερευνητικό και πειραματικό στάδιο καθιστούν τον τομέα της Ιατρικής άρρηκτα συνδεδεμένο με εκείνον της Πληροφορικής. Ένα από τα φλέγοντα και ενδιαφέροντα ερευνητικά ζητήματα στον τομέα της Ιατρικής – συγκεκριμένα της νευρολογίας - είναι η λειτουργία του ανθρώπινου εγκεφάλου. Μια διαδεδομένη μέθοδος ανάλυσης της εγκεφαλικής δραστηριότητας τού ανθρώπου είναι η Λειτουργική Απεικόνιση Μαγνητικού Συντονισμού (fMRI). Είναι μη επεμβατική μέθοδος μέσω της οποίας μπορούμε να μελετήσουμε τις περιοχές του εγκεφάλου που ενεργοποιούνται κατά τη διάρκεια εκτέλεσης μιας ενέργειας (π.χ. ομιλία, παρατήρηση μιας εικόνας). Στην εργασία μας ασχολούμαστε με την εφαρμογή αλγορίθμων Dictionary Learning και Factorization σε fMRI. Πιο συγκεκριμένα επικεντρωνόμαστε στους αλγορίθμους k-SVD, MM και PARAFAC2. Στόχος μας είναι η επιτάχυνση των παραπάνω αλγορίθμων μέσω της χρήσης κάρτας γραφικών, η οποία παρέχει τη δυνατότητα πολλαπλών παράλληλων πράξεων πάνω σε ογκώδη δεδομένα. Τα πειράματα μας διενεργήθηκαν με χρήση CUDA και Matlab.The remarkable progress observed in medicine over the years is related to the rapid and widespread deployment of computer use in health sciences (Medicine, Biology, Biotechnology). The complex calculations required at the research and experimental stages make the field of medicine inextricably linked to that of computer technology. One of the burning and interesting research issues in the medical field is the function of the human brain. A widespread method of analyzing human brain activity is functional Magnetic Resonance Imaging (fMRI). It is a non-invasive method through which we can study the brain regions that are activated during the performance of an activity (for example speech, observation of an image). In our thesis we deal with the implementation of Dictionary Learning and Factorization algorithms in fMRI. Specifically, we focus on k-SVD, MM and PARAFAC2 algorithms. Our goal is to accelerate the above algorithms through the use of GPU, which offers the capability of multiple parallel operations over big data. Our experiments were conducted using CUDA and Matlab

Cushing's syndrome in pregnancy: a review of reported cases

Cushing’s syndrome (CS) causes hypogonadotropic hypogonadism and anovulatory infertility due to hypercortisolism, and it is very rare in pregnancy. CS in pregnancy is associated with important maternal-foetal morbidity and mortality, such as preeclampsia and premature delivery. A systematic search was conducted in the MEDLINE library to retrieve articles reporting cases of CS in pregnant women, during the period between 2010 and 2020.Thirty-five reported cases are presented focusing on the ability of diagnosis, treatment therapies, and foetal outcomes. Diagnosis of CS during pregnancy can be challenging and is often delayed, adrenal adenoma being the predominant cause. Both medical treatment and surgery aiming at restoring the cortisol balance reduce maternal and foetal complications

Histone Deacetylases and their Inhibitors in Colorectal Cancer Therapy: Current Evidence and Future Considerations.

Colorectal cancer (CRC) comprises a heterogeneous group of gastrointestinal tract tumors. It is a multifactorial disease, and a plethora of distinct factors are involved in its pathogenesis and pathophysiology. The development of CRC is not limited to genetic changes, but epigenetic and environmental factors are also involved. Among the epigenetic factors, histone deacetylases (HDACs), a group of epigenetic enzymes that regulate gene expression, have been reported to be over-expressed in CRC. HDACs and their inhibitors seem to play an important role in the molecular pathophysiology of CRC. The aim of this review was to define the role of HDAC inhibitors as potential anticancer agents against CRC

Cushing's syndrome in pregnancy: a review of reported cases

Cushing's syndrome (CS) causes hypogonadotropic hypogonadism and anovulatory infertility due to hypercortisolism, and it is very rare in pregnancy. CS in pregnancy is associated with important maternal-foetal morbidity and mortality, such as preeclampsia and premature delivery. A systematic search was conducted in the MEDLINE library to retrieve articles reporting cases of CS in pregnant women, during the period between 2010 and 2020. Thirty-five reported cases are presented focusing on the ability of diagnosis, treatment therapies, and foetal outcomes. Diagnosis of CS during pregnancy can be challenging and is often delayed, adrenal adenoma being the predominant cause. Both medical treatment and surgery aiming at restoring the cortisol balance reduce maternal and foetal complications

The Role of TPOAb in Thyroid-Associated Orbitopathy: A Systematic Review

Introduction: Thyroid-associated orbitopathy (TAO) is one of the most common autoimmune inflammatory disorders of the orbit. The presence of anti-thyroid antibodies is believed to play a role in the pathogenesis and clinical status of the TAO patients. Herein, we review the usefulness of TPOAb as a biomarker for TAO. Methods: A systematic search in MEDLINE library was conducted. Results: Twenty studies were included. TPO is expressed in orbital tissues, and the polymorphism rs11675434 SNP has proven to be associated with clinically evident TAO. Studies in pediatric patients have shown a positive correlation between high TPOAb levels and TAO. In contrast, results in adults are inconsistent. Some studies imply a protective role of TPOAb, yet the majority did not find any association. Some authors have suggested an implication of TPOAb in the pathophysiology of TAO in TRAb-negative patients. Conclusions: The role of TPOAb in TAO remains unclear and controversial

Concomitant Existence of Bilateral Adrenal Adenomas. To Operate or Not?

Nowadays, through the wide use of both magnetic resonance imaging and computed tomography, the diagnosis of adrenal incidentaloma is becoming increasingly frequent. Pheochromocytomas are neuroendocrine tumors which produce catecholamine, and they are characterized by headaches, palpitations, sweating and hypertension. Aldosterone-secreting adrenal cortical adenomas can cause various metabolic and cardiovascular diseases due to aldosterone excess. Our aim is to present a rare case of a concomitant existence of pheochromocytoma in the right adrenal and a functioning adrenal cortical adenoma in the left, worthwhile mentioning since the appearance of these two entities in different location in the same patient is unprecedented. The treatment remains challenging

Government Debt Crisis and the Impact on National Health Systems: A Retrospective Study and Policy Recommendations to Greece

This article aims to explore the impact of the government debt crisis on the national health system (NHS) using a representative sample of respondents in Greek hospitals and provides certain suggestions regarding health policies that could be implemented at the national or local level. This study was conducted at the Evangelismos & Eye Polyclinic of Athens General Hospital in Athens, Greece. The study period was January and February of 2016, and the study included 600 outpatients who frequently submitted to follow-ups and consented to participate. Based on the results of this study, the participants had an average health status, while 94.2% of them had medical insurance. The predominant reason (88%) for choosing public hospitals instead of private practices was insufficient income. Further investigation revealed a significant positive correlation between the participant’s age and the number of hospital visits, the number of medical tests performed, and their satisfaction from the health services provided. Finally, a probit-model was used in order to study factors that could potentially influence their level of satisfaction from the services they used

Clinical Significance of the Histone Deacetylase 2 (HDAC-2) Expression in Human Breast Cancer

Background/Aim: There is a strong association between malignancy and histone deacetylases (HDACs). Histone deacetylase inhibitors (HDACIs) are now being tested as antitumor agents in various clinical trials. We aimed to assess the clinical importance of HDAC-2 in breast cancer (BC). Materials and Methods: A total of 118 BC specimens were examined immunohistochemically. A statistical analysis was conducted in order to examine the relation between HDAC-2 and the clinicopathological features and survival of the patients. Results: Higher HDAC-2 expression was related to lobular histological type of cancer, grade III, and stage III BC. In addition, the disease-free period and overall survival were curtailed and negatively related to the over-expression of HDAC-2. Other factors correlating with worse survival were histological types other than ductal or lobular, and the stage of the disease. Conclusions: This study showed a relationship between HDAC-2 and BC. Further studies are required in order to eventually potentiate the role of HDACIs as anticancer agents in BC