Choose your Data Wisely: A Framework for Semantic Counterfactuals

Counterfactual explanations have been argued to be one of the most intuitive forms of explanation. They are typically defined as a minimal set of edits on a given data sample that, when applied, changes the output of a model on that sample. However, a minimal set of edits is not always clear and understandable to an end-user, as it could, for instance, constitute an adversarial example (which is indistinguishable from the original data sample to an end-user). Instead, there are recent ideas that the notion of minimality in the context of counterfactuals should refer to the semantics of the data sample, and not to the feature space. In this work, we build on these ideas, and propose a framework that provides counterfactual explanations in terms of knowledge graphs. We provide an algorithm for computing such explanations (given some assumptions about the underlying knowledge), and quantitatively evaluate the framework with a user study.Comment: To appear at IJCAI 202

Amphetamine Use Revealing Hypertrophic Cardiomyopathy in a Young Patient.

Adrenergic overstimulation in long term can lead to a hyperdynamic myocardium and give rise to hypertrophy and ultimately to heart failure. Amphetamine use is a common cause of neurohormonal activation, which gives rise to such adverse cardiovascular events. However, hypertrophy of myocardium in young patients, even due to apparently obvious causes, should always be considered as a red flag and a further diagnostic downstream should take place, in order to exclude genetic causes. We present a case of a young man with chronic use of amphetamine and an incidental finding of hypertrophic cardiomyopathy

"Broken Heart" and "Broken Brain": Which Connection?

The interconnections between brain and heart are increasingly recognized. Takotsubo cardiomyopathy, also known as "broken heart syndrome", is characterized by a cardiovascular dysfunction provoked by an emotional or stressful situation. Similar events can trigger a neurological pathology called transient global amnesia. These conditions can occur simultaneously, although their precise connection is not well understood. We aim to present the case of a patient who experienced them and to review the relevant literature

Endoscopic treatment of gastro-esophageal reflux disease: biocompatibility control of subcutaneously implanted materials in LES

Background. A gelatinous implant containing polymethylmethacrylate (PMMA) beads is already successfully used to augment the diminished thickness of chorium in skin defects and wrinkles. The present study aims to determine whether the submucosal injection of PMMA microspheres into the lower esophageal folds could offer support to the Lower Esophageal Sphincter (LES) and decrease the severity of symptoms of Gastro Esophageal Reflux Disease (GERD). Methods. Endoscopic submucosal implantation of PMMA was carried out in 10 Proton Pump Inhibitors (PPI) dependent or refractory refluxing patients. Assessment of the symptom severity score together with 24hr pH monitoring, upper GI endoscopy and endoscopic Ultrasound were performed to evaluate the efficacy of implantation. Results. A decrease in the severity of GERD symptoms associated with a fall in the mean total time with pH<4 was noted after the implantation of PMMA in a statistically significant degree (p<0,05). Seven patients out of ten, were off all medications after the implantation. Serious procedure related complications were not met. Conclusions. Endoscopic implantation of PMMA into the submucosa of the lower esophageal folds could possibly be a new method of treating GERD. Further studies are required to determine the longterm efficacy of the procedure.Αναδρομή: Το νέο πεδίο έρευνας στη θεραπεία της γαστροοισοφαγικής παλινδρομικής νόσου αφορά ενδοσκοπικές τεχνικές ενίσχυσης του κατώτερου οισοφαγικού σφικτήρα. Σκοπός: Πειραματικό σκέλος. Η μελέτη της βιοσυμβατότητας ενέσεων προσθετικών υλικών υποβλεννογονίως και κατά τη γαστροοισοφαγική συμβολή. Κλινικό σκέλος. Η αποτελεσματικότητα της ενδοσκοπικής εμφύτευσης PMMA στον υποβλεννογονίο του κατώτερου οισοφάγου στην ύφεση των συμπτωμάτων της ΓΟΠΝ. Ασθενείς και μέθοδος: Πειραματικό σκέλος. Εμφύτευση Macroplastique σε 6 οικιακούς χοίρους. Λήψη παρασκευασμάτων σε διαστήματα 1 μηνός. Κλινικός σκέλος. Ενδοσκοπική εμφύτευση PMMA υποβλεννογονίως κατά την καρδιοοισοφαγική συμβολή. Μελέτη επίδραση στην κλίμακα συμπτωμάτων, την 24ωρη pHμετρία, την ενδοσκοπική και υπερηχογραφική εικόνα. Αποτελέσματα. Πειραματικό σκέλος. Επιβεβαίωση της βιοσυμβατότητας του υλικού, αναγνώριση ανάπτυξης συνδετικού ιστού στο γαστρικό τοίχωμα μετά 6 μήνες. Κλινικό σκέλος. Επιτυχής πραγματοποίηση της εμφύτευσης σε 10 ασθενείς. Η κλίμακα βαρύτητας συμπτωμάτων, ο % χρόνος με pH<4 , και το DeMeester Score βελτιώθηκαν σε στατιστικά σημαντικό βαθμό. 7 από του 10 ασθενείς ήσαν ελεύθεροι φαρμακευτικής αγωγή 14,5 μήνες μετά τη θεραπεία. Συμπεράσματα. Η ενδοσκοπική εμφύτευση βιοσυμβατών υλικών στον κατώτερο οισοφάγο μπορεί να θεωρείται γέφυρα ανάμεσα στη φαρμακευτική και τη χειρουργική θεραπεία

Multi-Modal Song Mood Detection with Deep Learning

The production and consumption of music in the contemporary era results in big data generation and creates new needs for automated and more effective management of these data. Automated music mood detection constitutes an active task in the field of MIR (Music Information Retrieval). The first approach to correlating music and mood was made in 1990 by Gordon Burner who researched the way that musical emotion affects marketing. In 2016, Lidy and Schiner trained a CNN for the task of genre and mood classification based on audio. In 2018, Delbouys et al. developed a multi-modal Deep Learning system combining CNN and LSTM architectures and concluded that multi-modal approaches overcome single channel models. This work will examine and compare single channel and multi-modal approaches for the task of music mood detection applying Deep Learning architectures. Our first approach tries to utilize the audio signal and the lyrics of a musical track separately, while the second approach applies a uniform multi-modal analysis to classify the given data into mood classes. The available data we will use to train and evaluate our models comes from the MoodyLyrics dataset, which includes 2000 song titles with labels from four mood classes, {happy, angry, sad, relaxed}. The result of this work leads to a uniform prediction of the mood that represents a music track and has usage in many applications

Unusual site of recurrent musculoskeletal hydatid cyst: Case report and brief review of the literature

A case of a large multiplex recurrent hydatid cyst involving the left gluteal muscle and the left iliopsoas, accompanied with degeneration of the musculature of the left upper leg is presented along with a review of the relevant literature. Very few such cases have been reported worldwide. The presented case is also distinguished by the involvement of muscles of distant anatomic areas. (C) 2006 The WJG Press. All rights reserved