Filters
total: 26623
-
Catalog
- Publications 4512 available results
- Journals 1174 available results
- Conferences 56 available results
- People 157 available results
- Projects 26 available results
- Research Teams 2 available results
- e-Learning Courses 115 available results
- Events 14 available results
- Open Research Data 20567 available results
displaying 1000 best results Help
Search results for: federated learning , breast cancer , health industry , image classification , mammography , deep learning
-
Altered circadian genes expression in breast cancer tissue according to the clinical characteristics
Publication -
The impact of the Polish mass breast cancer screening program on prognosis in the Pomeranian Province
Publication -
Prognostic Significance of TOP2A Gene Dosage in HER-2-Negative Breast Cancer
Publication -
Application of a three‑dimensional (3D) breast cancer model to study macrophage polarization
Publication -
FGF7 / FGFR2 – JunB signalling counteracts the effect of progesterone in luminal breast cancer
Publication -
Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
-
Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
-
Journal of Classification
Journals -
Anita Maria Dąbrowicz-Tlałka dr
PeopleAnita Dąbrowicz-Tlałka graduated from the Faculty of Mathematics and Physics at the University of Gdańsk with an outstanding grade, having written her thesis in the field of geometric topology. She concurrently obtained a diploma in Postgraduate Studies in the Basics of Computer Science at the University of Gdańsk. In 2001 she received a Ph.D. degree in mathematical studies at the Poznań University of Technology after defending...
-
Becoming a Learning Organization Through Dynamic Business Process Management
Publication -
The detection of Alternaria solani infection on tomatoes using ensemble learning
Publication -
Scheduling Repetitive Construction Processes Using the Learning-Forgetting Theory
Publication -
Meta-Design and the Triple Learning Organization in Architectural Design Process
Publication -
Agent-Based Population Learning Algorithm for RBF Network Tuning
Publication -
Digital competence learning in secondary adult education in Finland and Poland
Publication -
An A-Team approach to learning classifiers from distributed data sources
Publication -
An A-Team Approach to Learning Classifiers from Distributed Data Sources
Publication -
Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
-
Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublicationPrzedstawiono dydaktyczne modele symulacyjne wykorzystywane w zdalnym kształceniu z zakresu informatyki i technik komunikacyjnych. Pokazano na przykładach zbudowanych symulatorów, w jaki sposób zrealizować lub dostosować modele symulacyjne do zdalnego nauczania. Opisano doświadczenia autorów w wykorzystaniu modeli symulacyjnych w zdalnym nauczaniu.
-
European Journal of Breast Health
Journals -
Metal–Organic Frameworks (MOFs) for Cancer Therapy
PublicationMOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...
-
An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
-
An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
-
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
-
Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
-
Survival time prognosis under a Markov model of cancer development
PublicationIn this study we look at a breast cancer data set of women from Pomerania region collected in year 1987-1992 in the Medical University of Gdańsk. We analyze the clinical risk factors in conjunction with Markov model of cancer development. We evaluate Artificial Neural Network (ANN) survival time prediction via a simulation study.
-
DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
-
Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed
Publication -
Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublicationThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
-
Juices from untypical edible fruits as acidity regulators for food industry. Verification of health promoting properties. Comparison with typical acidity regulators.
PublicationNowadays all kind of food additives, and among them acidity regulators, have become necessary components of most food products. Their role is lengthening shelf-life, improving the sensory properties and protecting food products from microbial contaminations. However, despite advantages, there are also some undesirable effects of use of food additives that have raised public concern recently. Therefore, food industry considers the...
-
Active dynamic thermography method for TRAM flap blood perfusion mapping in breast reconstruction
PublicationThis paper presents the new method of the transverse rectus abdominis musculocutaneous flap blood perfusion mapping based on the active dynamic thermography. The method is aimed at aiding a surgeon during breast reconstruction procedure. A pair of dTnorm and t90_10 parameters were used as parametric image descriptors of the flap blood perfusion. The method was tested on 38 patients that were subjected to breast reconstruction procedure....
-
Image Processing in Robotics
e-Learning Courses -
Image Processing in Robotics
e-Learning Courses -
Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
-
Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
Publication -
BREAST
Journals -
Near-Infrared Fluorescence Image-Guided Surgery in Esophageal and Gastric Cancer Operations
Publication -
Prognostic Value of TOP2A Gene Amplification and Chromosome 17 Polysomy in Early Breast Cancer
Publication -
Aggressive Phenotype of Cells Disseminated via Hematogenous and Lymphatic Route in Breast Cancer Patients
Publication -
Rapana thomasiana hemocyanin modified with ionic liquids with enhanced anti breast cancer activity
Publication -
Sulforaphene, an isothiocyanate present in radish plants, inhibits proliferation of human breast cancer cells
Publication -
Physical and psychological impairments of women with upper limb lymphedema following breast cancer treatment
Publication -
Effective kernel‐principal component analysis based approach for wisconsin breast cancer diagnosis
Publication -
Nanosized zinc, epigenetic changes and its relationship with DMBA induced breast cancer in rats
Publication -
Physical activity, life satisfaction and adjustment to illness in women after treatment of breast cancer
Publication -
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...
-
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...
-
Reward Learning Requires Activity of Matrix Metalloproteinase-9 in the Central Amygdala
Publication -
Efficient sampling of high-energy states by machine learning force fields
Publication -
IT support for OKNO broadband Internet-based distant learning system at WUT
Publication