An Interpretable Multiple-Instance Approach for the Detection of referable Diabetic Retinopathy from Fundus Images

Diabetic Retinopathy (DR) is a leading cause of vision loss globally. Yet despite its prevalence, the majority of affected people lack access to the specialized ophthalmologists and equipment required for assessing their condition. This can lead to delays in the start of treatment, thereby lowering their chances for a successful outcome. Machine learning systems that automatically detect the disease in eye fundus images have been proposed as a means of facilitating access to DR severity estimates for patients in remote regions or even for complementing the human expert's diagnosis. In this paper, we propose a machine learning system for the detection of referable DR in fundus images that is based on the paradigm of multiple-instance learning. By extracting local information from image patches and combining it efficiently through an attention mechanism, our system is able to achieve high classification accuracy. Moreover, it can highlight potential image regions where DR manifests through its characteristic lesions. We evaluate our approach on publicly available retinal image datasets, in which it exhibits near state-of-the-art performance, while also producing interpretable visualizations of its predictions.Comment: 11 page

Resistant Hypertension Workup and Approach to Treatment

Resistant hypertension is defined as blood pressure above the patient's goal despite the use of 3 or more antihypertensive agents from different classes at optimal doses, one of which should ideally be a diuretic. Evaluation of patients with resistive hypertension should first confirm that they have true resistant hypertension by ruling out or correcting factors associated with pseudoresistance such as white coat hypertension, suboptimal blood pressure measurement technique, poor adherence to prescribed medication, suboptimal dosing of antihypertensive agents or inappropriate combinations, the white coat effect, and clinical inertia. Management includes lifestyle and dietary modification, elimination of medications contributing to resistance, and evaluation of potential secondary causes of hypertension. Pharmacological treatment should be tailored to the patient's profile and focus on the causative pathway of resistance. Patients with uncontrolled hypertension despite receiving an optimal therapy are candidates for newer interventional therapies such as carotid baroreceptor stimulation and renal denervation

Efficient Distributed Outlier Detection in Data Streams

Anomaly detection is one of the major data mining tasks in modern applications. An element that shows significant deviation from the "usual" behavior is marked as an outlier. This means that this element either corresponds to noise or it requires more careful examination because it may be important. Also, many clustering algorithms are very sensitive to outliers. In any case, outliers must be identified and explored further, meaning that efficient outlier mining techniques are required. In this paper, we focus on distributed density-based outlier detection over multi-dimensional data streams. In particular, we focus on the approximation method for computing the Local Correlation Integral (LOCI) of multi-dimensional points. Each object p is assigned a score score(p) which represents the outlier score of p. Thus, one can select the top-k elements from the dataset that have the highest outlier scores. Our proposal has been implemented in Apache Spark using Scala and experiments have been conducted in a physical cluster running Apache Hadoop 2.7 and Apache Spark 2.4.0. Performance evaluation results demonstrate that the proposed algorithm is efficient and scalable and therefore it can be used to mine outliers in large distributed datasets

Η εγκατάσταση σταθμών βάσης κινητής τηλεφωνίας και η προστασία του περιβάλλοντος και της ανθρώπινης υγείας

Σκοπός της παρούσας διπλωματικής εργασίας είναι η διερεύνηση του αν το ελληνικό πλαίσιο για την εγκατάσταση σταθμών βάσης κινητής τηλεφωνίας προστατεύει αποτελεσματικά το περιβάλλον και την ανθρώπινη υγεία. Η συνεχής τεχνολογική αναβάθμιση οδήγησε στην έλευση του 5G, ετοιμάζοντας τις σύγχρονες κοινωνίες για τον ψηφιακό μετασχηματισμό τους. Ωστόσο, σύμφωνα με την επιστημονική κοινότητα, οι επιτπώσεις από την ανάπτυξη και λειτουργία των ειδικών δικτύων που απαιτούν οι ηλεκτροινικές επικοινωνίες, είναι ακόμη άγνωστες. Πράγματι, τα ηλεκτρομαγνητικά πεδία, τα οποίά προκύπτουν καθώς το σήμα μεταδίδεται από τις κεραίες στις τερματικές συσκεύες, μπορούν να προκαλέσουν βλάβη στο περιβάλλον και την ανθρώπινη υγεία, όταν δεν τηρούνται οι προδιαγραφές ασφαλείας. Αφού αναλύσαμε τις διαφορετικές φάσεις που πέρασε η εθνική νομοθεσία (από το Ν. 1650/1986 έως σήμερα), συμπεραίνουμε ότι οι οι όροι προστασίας τηρούνται πλήρως στην Ελλάδα. Εφαρμοζοντας τη θεμελιώδη αρχή της Προφύλαξης και συμμορφούμενο με τις ενωσιακές διατάξεις σχετικά με τη μείωση της έκθεσης στα ηλεκτρομαγνητικά πεδία, το εθνικό αδειοδοτικό πλαίσιο έχει γίνει αυστηρότερο ανά τις δεκαετίες, αναγνωρίζοντας τις ενδεχόμενες αρνητικές συνέπειες στα φυσικά οικοσυστήματα και την ανθρώπινη υγεία. Επομένως, ένα επίπεδο αποτελεσματικής προστασίας επιτυγχάνεται στην Ελλάδα, διασφαλίζοντας προδιαγραφές ασφαλείας για την εγκατάσταση σταθμών βάσης κινητής τηλεφωνίας και την ανάπτυξη του δικτύου 5G.This Master Thesis aims to investigate whether the Greek policy and legal framework for mobile telephony antennas installations effectively protect the environment and human health. The constant improvement of the technology used in electronic communications has led to the advent of 5G, signifying the digital transformation of modern societies. However, according to the scientific community, the consequences of developing and operating the special networks that the electronic communications demand to work are still unknown. It is true that Electromagnetic Fields (EMF’s), created whilst the signal is transmitted via antennas to mobile devices, may cause damage to the environment and the human health when safety conditions are not followed. After analyzing the different phases the Greek relevant legislation went through (from the Act No. 1650/1986 till today), we concluded that protection standards are fully respected in Greece. Implementing the fundamental principle of Precaution and abiding by the EU provisions for limiting of exposure to EMF’s, the domestic licensing framework has become stricter throughout the decades, recognizing the possible negative effects on natural habitats (emphasizing on sensitive areas, i.e. NATURA 2000), as well as on human health. Therefore, a level of sufficient protection is achieved in Greece, guarantying safety standards for the mobile telephony antennas installations and the gradual deployment of 5G

Continuous Outlier Mining of Streaming Data in Flink

In this work, we focus on distance-based outliers in a metric space, where the status of an entity as to whether it is an outlier is based on the number of other entities in its neighborhood. In recent years, several solutions have tackled the problem of distance-based outliers in data streams, where outliers must be mined continuously as new elements become available. An interesting research problem is to combine the streaming environment with massively parallel systems to provide scalable streambased algorithms. However, none of the previously proposed techniques refer to a massively parallel setting. Our proposal fills this gap and investigates the challenges in transferring state-of-the-art techniques to Apache Flink, a modern platform for intensive streaming analytics. We thoroughly present the technical challenges encountered and the alternatives that may be applied. We show speed-ups of up to 117 (resp. 2076) times over a naive parallel (resp. non-parallel) solution in Flink, by using just an ordinary four-core machine and a real-world dataset. When moving to a three-machine cluster, due to less contention, we manage to achieve both better scalability in terms of the window slide size and the data dimensionality, and even higher speed-ups, e.g., by a factor of 510. Overall, our results demonstrate that oulier mining can be achieved in an efficient and scalable manner. The resulting techniques have been made publicly available as open-source software

A Flail Tricuspid Valve

A 30-year-old man was admitted to the hospital because of palpitations. He had a life-threatening liver rupture five years earlier, after a massive uncontrolled explosion of a big bunch of fireworks. Transthoracic echocardiography revealed severe tricuspid regurgitation due to a flail anterior leaflet of the tricuspid valve. Transesophageal echocardiography had an additive imaging value in demonstrating additionally a flail posterior leaflet. Flail tricuspid valve causing severe regurgitation is usually due to mechanical trauma. Since it is well tolerated for years, the diagnosis may be delayed or missed entirely. Echocardiography has allowed easier diagnosis of this condition resulting in earlier and, hence, more effective treatment