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Search results for: e. coli, machine learning, optical method, spectroscopy, urine, urospesis
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Brygida Mielewska dr
PeopleBorn on 1 December 1972 in Gdynia. Education and professional experience:June 1997 MSc in Physics, Gdańsk University, Faculty of Mathematics and Physics; October 1997 – August 2003 – Assistant at Gdańsk University of Technology (GUT), Faculty of Applied Physics nad Technical Mathematics, Department of Physics of Electronic Phenomena;June 2003 – PhD in Physics, thesis advisor prof. dr hab. Mariusz Zubek; September 2003- January...
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Adam Władziński
PeopleAdam Władziński, a PhD Candidate at Gdansk University of Technology, specializes in Biomedical Engineering with a focus on machine learning for image processing and blockchain technology. Holding a BEng and MSc in Electronics, Adam Władziński has developed a keen interest in applying advanced computational techniques to biological systems. During their master’s program, Adam Władziński explored laser spectroscopy, building a database...
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Importance of biofilm formation by uropathogenic E. coli Dr+ strains in urinary tract infections
PublicationImportance of biofilm formation by uropathogenic E. coli Dr+ strains in urinary tract infections
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C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning
PublicationThe rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation of various origins, oncological, cardiovascular, bacterial or viral events. In this study, we describe an interferometric sensor able to detect the CRP level for distinguishing between...
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Paweł Możejko dr hab.
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje
PublicationGeneratywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...
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Maciej Wróbel dr inż.
PeopleReceived PhD from Gdańsk University of Technology in 2019. Research interests involve non-invasive applications of Raman spectroscopy for tissue analysis, specifically blood parameters measurements. Tissue mimicking phantoms, measurement of optical properties (scattering, absorption), as well as other optical sensing methods. Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) utilized for measurements of biological...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...