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Search results for: federated learning , breast cancer , health industry , image classification , mammography , deep learning
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Targeting shelterin proteins for cancer therapy.
PublicationAs a global health challenge, cancer prompts continuous exploration for innovative therapies that are also based on new targets. One promising avenue is targeting the shelterin protein complex, a safeguard for telomeres crucial in preventing DNA damage. The role of shelterin in modulating ataxia- telangiectasia mutated (ATM) and ataxia-telangiectasia and Rad3-related (ATR) kinases, key players in the DNA damage response (DDR),...
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Near-Infrared Fluorescence Image-Guided Surgery in Esophageal and Gastric Cancer Operations
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Patient with metastatic breast cancer presenting as acute cholecystitis with one-year survival on hormonotherapy
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Prognostic Value of TOP2A Gene Amplification and Chromosome 17 Polysomy in Early Breast Cancer
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Aggressive Phenotype of Cells Disseminated via Hematogenous and Lymphatic Route in Breast Cancer Patients
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Rapana thomasiana hemocyanin modified with ionic liquids with enhanced anti breast cancer activity
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Sulforaphene, an isothiocyanate present in radish plants, inhibits proliferation of human breast cancer cells
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Physical activity, life satisfaction and adjustment to illness in women after treatment of breast cancer
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Effective kernel‐principal component analysis based approach for wisconsin breast cancer diagnosis
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Physical and psychological impairments of women with upper limb lymphedema following breast cancer treatment
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Nanosized zinc, epigenetic changes and its relationship with DMBA induced breast cancer in rats
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Analysis of transient thermal processes for improved visualization of breast cancer using IR imaging.
PublicationPrzedstawiono analizę możliwości i ograniczeń metod termograficznych w diagnostyce nowotworów piersi. Przeanalizowane termiczne modele numeryczne piersi z nowotworem pokazują, iż zastosowanie nowej metody aktywnej termografii dynamicznej z termicznym wymuszeniem zewnętrznym, może znacząco poprawić skuteczność wykrywania nowotworów piersi we wczesnym stadium ich rozwoju . Pokazano również wyniki badania klinicznego pacjentki...
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Juices from non-typical edible fruits as health-promoting acidity regulators for food industry
PublicationThe study verifies the possibility of application of juices from selected fruits characterized by the high antioxidant potential as natural acidity regulators with improved nutritional properties. The tested non-typical fruits included mirabelle plum, sea buckthorn and blue-berried honeysuckle. Beetroot juice whose pH is about 6.0 served as a model food product. Potentiometric titration was used to compare the efficacy of tested...
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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Modular machine learning system for training object detection algorithms on a supercomputer
PublicationW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Beesybees-Agent-Based, Adaptive & Learning Workflow Execution Module for BeesyCluster
PublicationPrezentujemy projekt oraz implementację adaptacyjnego i uczącego się modułu przeznaczonego dowykonywania scenariuszy w środowisku BeesyCluster. BeesyCluster pozwala na modelowaniescenariuszy w formie acyklicznego grafu skierowanego, w którym wierzchołki oznaczają zadania,a krawędzie określają zależności między nimi. Przedstawiamy także kooperatywne wykonaniescenariusza przez grupę agentów zdolnych do zbierania, składowania i korzystania...
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IT support for OKNO broadband Internet-based distant learning system at WUT
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Reward Learning Requires Activity of Matrix Metalloproteinase-9 in the Central Amygdala
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A Prototype of Educational Agent in Distance Learning Environment - Virtual Student Assistant
PublicationW zdalnym nauczaniu pojawia się wiele systemów wspierających, z których niezwykle ciekawym przykładem są agenty edukacyjne. Wśród wielu rodzajów agentów edukacyjnych wyróżnia się osobistych asystentów, których rolą jest organizacyjna pomoc osobie zdobywającej wiedzę. Artykuł jest poświęcony zaimplementowanemu na Wydziale ETI Politechniki Gdańskiej prototypowi agenta edukacyjnego o nazwie WAS (Wirtualny Asystent Studenta). Pokazana...
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Efficient sampling of high-energy states by machine learning force fields
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The Role of Dopaminergic Genes in Probabilistic Reinforcement Learning in Schizophrenia Spectrum Disorders
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Confirmation Bias in the Course of Instructed Reinforcement Learning in Schizophrenia-Spectrum Disorders
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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E-learning - prawdziwa czy fikcyjna koncepcja edukacyjnego rozwoju uczelni
PublicationNie można zaprzeczyć, że wykorzystanie narzędzi multimedialnych oraz Internetu pozwala na dodanie istotnych, z punku widzenia dydaktyki, komponentów edukacyjnych tworzących kompetencje i umiejętności zawodowe, a także te czysto akademickie. Trzeba rozważyć, czy wszystkie strony procesu dydaktycznego na uczelni są przygotowane do e−learningu. Oczywistym wymogiem jest posiadanie odpowiedniej bazy sprzętowej i przygotowanej kadry...
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Analysis of network infrastructure and QoS requirements for modern remote learning systems.
PublicationW referacie przedstawiono różne modele zdalnego nauczania. Podjęto próbę oceny wymagań nakładanych na infrastrukturę sieci. Ponadto przedstawiono mechanizmy QoS spotykane w sieciach teleinformatycznych oraz dokonano oceny możliwości ich współpracy w systemach edukacji zdalnej
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Developing ICT-rich lifelong learning opportunities trough EU-projects.
PublicationArtykuł opisuje doświadczenia Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej od 1997 roku we wdrażaniu kształcenia na odległość. Głównym zadaniem CEN PG jest tworzenie dostępu do materiałów, skryptów, kursów i środowiska internetowego w sieciach LAN i WAN. Udostępniane moduły kursowe zostały opracowane głównie w międzynarodowych zespołach projektowych w wyniku realizowanych unijnych programów Leonardo da Vinci, Socrates...
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A Note on Knowledge Management Education: Towards Implementing Active Learning Methods
PublicationKnowledge Management as an area of education is still a big challenge for teachers and practitioners. Nevertheless, there are several useful teaching methods in active education, especially oriented towards courses where innovation and delivering dynamic knowledge are critical. The goal of the paper is to present and discuss criteria relevant in the selection of active educational methods supporting knowledge management courses....
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Objects classification based on their physical sizes for detection of events in camera images
PublicationIn the paper, a method of estimation of the physical sizes of the objects tracked in the video surveillance system, and a simple module for object classification based on the estimated physical sizes, are presented. The results of object classification are then used for automatic detection of various types of events in the camera image.
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Cancer immune escape: the role of antigen presentation machinery
PublicationThe mechanisms of antigen processing and presentation play a crucial role in the recognition and targeting of cancer cells by the immune system. Cancer cells can evade the immune system by downregulating or losing the expression of the proteins recognized by the immune cells as antigens, creating an immunosuppressive microenvironment, and altering their ability to process and present antigens. This review focuses on the mechanisms...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublicationPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublicationThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Cancer-selective, single agent chemoradiosensitising gold nanoparticles
PublicationTwo nanometre gold nanoparticles (AuNPs), bearing sugar moieties and/or thiol-polyethylene glycol-amine (PEG-amine), were synthesised and evaluated for their in vitro toxicity and ability to radiosensitise cells with 220 kV and 6 MV X-rays, using four cell lines representing normal and cancerous skin and breast tissues. Acute 3 h exposure of cells to AuNPs, bearing PEG-amine only or a 50:50 ratio of alpha-galactose derivative and...
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Biological effects in photodynamic treatment combined with electropermeabilization in wild and drug resistant breast cancer cells
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A different methylation profile of circadian genes promoter in breast cancer patients according to clinicopathological features
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Tuning of the Anti-Breast Cancer Activity of Betulinic Acid via Its Conversion to Ionic Liquids
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Nanofiltration in the food industry
PublicationNanofiltration (NF), as a pressure-driven membrane process, has been widely demonstrated to have great potential for food processing applications. There are several advantages of this membrane process over traditional methods that makes NF suitable for food processing, such as the low thermal damage to the product, higher aroma retention, lower energy consumption, and low maintenance costs. In this chapter, according to the recent...
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Higher platelet counts correlate to tumour progression and can be induced by intratumoural stroma in non-metastatic breast carcinomas
PublicationBackground Platelets support tumour progression. However, their prognostic significance and relation to circulating tumour cells (CTCs) in operable breast cancer (BrCa) are still scarcely known and, thus, merit further investigation. Methods Preoperative platelet counts (PCs) were compared with clinical data, CTCs, 65 serum cytokines and 770 immune-related transcripts obtained using the NanoString technology. Results High normal...
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Framework for Structural Health Monitoring of Steel Bridges by Computer Vision
PublicationThe monitoring of a structural condition of steel bridges is an important issue. Good condition of infrastructure facilities ensures the safety and economic well-being of society. At the same time, due to the continuous development, rising wealth of the society and socio-economic integration of countries, the number of infrastructural objects is growing. Therefore, there is a need to introduce an easy-to-use and relatively low-cost...
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublicationThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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