Wyszukiwarka
Wyniki wyszukiwania dla: ANNOTATION MEDICAL DATA, CROWD-SOURCING
-
Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
-
Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
-
Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
-
Using Synchronously Registered Biosignals Dataset for Teaching Basics of Medical Data Analysis – Case Study
PublikacjaMedical data analysis and processing strongly relies on the data quality itself. The correct data registration allows many unnecessary steps in data processing to be avoided. Moreover, it takes a certain amount of experience to acquire data that can produce replicable results. Because consistency is crucial in the teaching process, students have access to pre-recorded real data without the necessity of using additional equipment...
-
BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
-
Data processing methods for dynamic medical thermography.
PublikacjaArtykuł przedstawia zastosowanie nowej metody syntezy obrazów w termografii dla potrzeb opisu ilościowego właściwości termicznych tkanek. Opis taki umożliwia różnicowanie przypadków medycznych. Metodę zastosowania dla licznych pomiarów fantomowych i in vitro w eksperymentach na zwierzętach (świnia domowa). Przedstawiono i omówiono rezultaty prac.
-
Interaction with medical data using QR-codes
PublikacjaBar-codes and QR-codes (Quick Response ) are often used in healthcare. In this paper an application of QR-codes to exchange of laboratory results is presented. The secure data exchange is proposed between a laboratory and a patient and between a patient and Electronic Health Records. Advanced Encryption Standard was used to provide security of data encapsulated within a QR-code. The experimental setup, named labSeq is described....
-
Scientific tools for collecting and analysing medical data in rhinology.
Publikacja -
Chest Injuries Based on Medical Rescue Team Data
Publikacja -
A survey of medical researchers indicates poor awareness of research data management processes and a role for data librarians
Publikacja -
Piotr Krajewski dr
OsobyPiotr Krajewski pracuje jako starszy bibliotekarz w Bibliotece Politechniki Gdańskiej. Jako pracownik Sekcji Informacji Naukowo-Technicznej skupia się przede wszystkim na zagadnieniach związanych z ruchem Open Access oraz rolą repozytoriów instytucjonalnych w jego rozwoju. Jest także autorem artykułów poruszających kwestie standaryzacji statystyk wykorzystania zasobów elektronicznych jak również problematykę „drapieżnych wydawców”....
-
Improving medical experts’ efficiency of misinformation detection: an exploratory study
PublikacjaFighting medical disinformation in the era of the pandemic is an increasingly important problem. Today, automatic systems for assessing the credibility of medical information do not offer sufficient precision, so human supervision and the involvement of medical expert annotators are required. Our work aims to optimize the utilization of medical experts’ time. We also equip them with tools for semi-automatic initial verification...
-
Magdalena Szuflita-Żurawska
OsobyMagdalena Szuflita-Żurawska jest kierownikiem Sekcji Informacji Naukowo-Technicznej na Politechnice Gdańskiej oraz Liderem Centrum Kompetencji Otwartej Nauki przy Bibliotece Politechniki Gdańskiej. Jej główne zainteresowania badawcze koncentrują się w obszarze komunikacji naukowej oraz otwartych danych badawczych, a także motywacji i produktywności naukowej. Jest odpowiedzialna między innymi za prowadzenie szkoleń dla pracowników...
-
Technical Engine for Democratization of Modeling, Simulations, and Predictions
PublikacjaComputational science and engineering play a critical role in advancing both research and daily-life challenges across almost every discipline. As a society, we apply search engines, social media, and se- lected aspects of engineering to improve personal and professional growth. Recently, leveraging such aspects as behavioral model analysis, simulation, big data extraction, and human computation is gain- ing momentum. The nexus...
-
Focus on Misinformation: Improving Medical Experts’ Efficiency of Misinformation Detection
PublikacjaFighting medical disinformation in the era of the global pandemic is an increasingly important problem. As of today, automatic systems for assessing the credibility of medical information do not offer sufficient precision to be used without human supervision, and the involvement of medical expert annotators is required. Thus, our work aims to optimize the utilization of medical experts’ time. We use the dataset of sentences taken...
-
The Crowd as a Source of Knowledge - From User Feedback to Fulfilling Requirements
PublikacjaCrowd-based and data-intensive requirements engineering (RE) strategy is an approach for gathering and analyzing information from the general public or the so-called crowd to derive validated user requirements. This study aims to conceptualize the process of analyzing information from a crowd to achieve the fulfillment of user requirements. The created model is based on the ADO framework (Antecedents-Decisions-Outcomes). In the...
-
Tomasz Dziubich dr inż.
OsobyWykonane projekty badawcze i celowe Internetowa platforma integracji danych i współpracy medycznych zespołów badawczych dla potrzeb ośrodków udarowych 2013 - 2016 MAYDAY EURO 2012 Superkomputerowa platforma kontekstowej analizy strumieni danych multimedialnych do identyfikacji wyspecyfikowanych obiektów lub niebezpiecznych zdarzeń – zadanie (Rozwój algorytmów i budowa aplikacji wspomagających badania medyczne), 2008-2012 Rozwój...
-
Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublikacjaA concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...
-
Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
-
Quantifying inconsistencies in the Hamburg Sign Language Notation System
PublikacjaThe advent of machine learning (ML) has significantly advanced the recognition and translation of sign languages, bridging communication gaps for hearing-impaired communities. At the heart of these technologies is data labeling, crucial for training ML algorithms on a huge amount of consistently labeled data to achieve models that generalize well. The adoption of language-agnostic annotations is essential to connect different sign...
-
Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
-
Mirosław Andrusiewicz prof. dr hab. n. med. i n. o zdr.
OsobyPosiadane dyplomy, stopnie naukowe lub artystyczne ̶ stopień doktora habilitowanego nauk medycznych (dyscyplina biologia medyczna) z dnia 4 grudnia 2017 r. Tytuł osiągnięcia naukowego: „Analiza wybranych genów związanych z przebiegiem zmian patologicznych w komórkach wywodzących się z żeńskich wewnętrznych narządów płciowych”; Uniwersytet Medyczny im. Karola Marcinkowskiego w Poznaniu, Wydział Lekarski II; recenzenci: Prof....
-
Rust QA: question answering dataset for "The Rust Programming Language" in SQuAD 2.0 format
Dane BadawczeRust QA is a dataset for training and evaluating QA systems. The dataset consists of 1068 questions to "The Rust Programming Language" book (https://doc.rust-lang.org/stable/book/) with the answers provided as text spans from the book. The dataset is released in SQuAD 2.0 format.
-
Towards Healthcare Cloud Computing
PublikacjaIn this paper we present construction of a software platform for supporting medical research teams, in the area of impedance cardiography, called IPMed. Using the platform, research tasks will be performed by the teams through computer-supported cooperative work. The platform enables secure medical data storing, access to the data for research group members, cooperative analysis of medical data and provide analysis supporting tools...
-
Leszek Dąbrowski dr inż.
OsobyLeszek Dąbrowski jest starszym wykładowcą w Katedrze Konstukcji Maszyn i Pojazdów. Ukończył studia w 1985 roku, pracę doktorską z tribologii (inżynierii łożyskowania) obronił w 1997 r. Prowadzi działalność dydaktyczną, inżynierską i badawczą w zakresie metod komputerowych w mechanice, biomechanice i inżynierii medycznej. Ostatnie prace badawcze dotyczą wykorzystania tomografii komputerowej i metody elementów skończonych w ortopedii...
-
Active Learning Based on Crowdsourced Data
PublikacjaThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...
-
Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
-
Framework for Integration Decentralized and Untrusted Multi-vendor IoMT Environments
PublikacjaLack of standardization is highly visible while we use historical data sets or compare our model with others that use IoMT devices from different vendors. The problem also concerns the trust in highly decentralized and anonymous environments where sensitive data are transferred through the Internet and then are analyzed by third-party companies. In our research we propose a standard that has been implemented in the form of framework...
-
Polyurethanes as a Potential Medical-Grade Filament for Use in Fused Deposition Modeling 3D Printers – a Brief Review
PublikacjaThe possibility of using 3D printing technology (3DP) in medical field is a kind of revolution in health care. This has contributed to a rapid growth in demand for 3D printers, whose systems and materials are adapted to strict medical requirements. In this paper, we report a brief review of polyurethanes as a potential medical-grade filament for use in Fused Deposition Modeling (FDM) 3D printer technology. The advantages of polyurethanes...
-
THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
-
A new approach to modeling of selected human respiratory system diseases, directed to computer simulations
PublikacjaThis paper presents a new versatile approach to model severe human respiratory diseases via computer simulation. The proposed approach enables one to predict the time histories of various diseases via information accessible in medical publications. This knowledge is useful to bioengineers involved in the design and construction of medical devices that are employed for monitoring of respiratory condition. The approach provides the...
-
DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe 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...
-
Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
PublikacjaML algorithms are very effective tools for medical data analyzing, especially at image recognition. Although they cannot be considered as a stand-alone diagnostic tool, because it is a black-box, it can certainly be a medical support that minimize negative effect of human-factors. In high-risk domains, not only the correct diagnosis is important, but also the reasoning behind it. Therefore, it is important to focus on trustworthiness...
-
The Impact of Foreign Accents on the Performance of Whisper Family Models Using Medical Speech in Polish
PublikacjaThe article presents preliminary experiments investigating the impact of accent on the performance of the Whisper automatic speech recognition (ASR) system, specifically for the Polish language and medical data. The literature review revealed a scarcity of studies on the influence of accents on speech recognition systems in Polish, especially concerning medical terminology. The experiments involved voice cloning of selected individuals...
-
Proposal of a Mobile Medical Waste Incinerator with Application of Automatic Waste Feeder and Heat Recovery System as a Novelty in Poland
PublikacjaThe paper presents and discusses the issues of medical waste (including hazardous ones) and the problems regarding their proper management in Poland. Inappropriate handling of infectious medical waste directly endangers human health and the environment. Infectious waste must be properly disposed of—in practice, the only method of their disposal available in Poland is a thermal treatment in the incinerators tailored for this purpose....
-
Analysis-by-synthesis paradigm evolved into a new concept
PublikacjaThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
-
Data Mining Applications and Methods in Medicine
PublikacjaIn this paper we describe the research area of data mining and its applications in medicine. The origins of data mining and its crucial features are shortly presented. We discuss the specificity of medicine as an application area for computer systems. Characteristic features of the medical data are investigated. Common problems in the area are also presented as well as the strengths and capabilities of the data mining methods....
-
Analysis of server-side and client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and geoportal
PublikacjaThe last decade has seen a rapid evolution of processing, analysis and visualization of freely available geographic data using Open Source Web-GIS. In the beginning, Web-based Geographic Information Systems employed a thick-client approach which required installation of platform-specific browser plugins. Later on, research focus shifted to platform-independent thin client solutions in which data processing and analysis was performed...
-
Proposal of a mobile medical waste incinerator with automatic waste feeder and heat recovery system
PublikacjaThe paper presents and discusses the issue of medical waste (including hazardous ones) and their proper management. Inappropriate handling of infectious medical waste directly endangers the human being health and the environment. Infectious waste must therefore be properly disposed of – one of the most commonly used methods is the thermal treatment in the incinerators tailored for this purpose. During designing an incinerator unit,...
-
A comprehensive evaluation of flexible FDM/FFF 3D printing filament as a potential material in medical application
PublikacjaThe use of FDM/FFF in 3D printing for medical sciences is becoming common. This is due to the high availability and decent price of both 3D printers and filaments useful for FDM/FFF. Currently, researchers' attention is focused mainly on the study of medical filaments based on PLA, PCL or their modifications. This contributes to insufficient diversity of medical-grade filaments on the market. Moreover, due to the lack of specified...
-
Platforma IPMed jako elastyczne źródło danych dla medycznych zespołów naukowych
PublikacjaPrzedstawiono architekturę rozproszonej platformy IPMed, która umożliwia akwizycję i przechowywanie zanonimizowanych danych medycznych. Pokazano wyniki zastosowania platformy w obszarze badań z zakresu hemodynamiki układu krążenia. Uzyskane dane pozwoliły na weryfikację hipotezy zespołu badawczego i określenie reguł rekomendacji w z leczeniu udarów.
-
ANYTIME POLYNOMIAL HEURISTIC ALGORITHM FOR PARTITIONING GROUPS OF DATA WITH PRESERVING CLASS PROPORTIONS FOR CROSS-VALIDATION
PublikacjaThe article describes a problem of splitting data for k-fold cross-validation, where class proportions must be preserved, with additional constraint that data is divided into groups that cannot be split into different cross-validation sets. This problem often occurs in e.g. medical data processing, where data samples from one patient must be included in the same cross-validation set. As this problem is NP-complete, a heuristic...
-
Multichannel Human Body Communication
PublikacjaHuman Body Communication is an attractive alternative for traditional wireless communication (Bluetooth, ZigBee) in case of Body Sensor Networks. Low power, high data rates and data security makes it ideal solution for medical applications. In this paper, signal attenuation for different frequencies, using FR4 electrodes, has been investigated. Performance of single and multichannel transmission with frequency modulation of analog...
-
The design of an intelligent medical space supporting automated patient interviewing
PublikacjaThe article presents the architecture and results of implementing an application for the intelligent medical space UbiDoDo (Ubiquitous Domestic Doctor's Office). The main purpose of the application is real-time monitoring of the biomedical parameters of a patient in his domestic environment. It allows an immediate reaction to appearing symptoms and provides means to automatically interview the patient and deliver his results to...
-
Online Interactivity – Shift Towards E-textbook-based Medical Education
PublikacjaTextbooks have played the leading role in academic education for centuries and their form has evolved, adapting to the needs of students, teachers and technological possibilities. Advances in technology have caused educators to look for new sources of knowledge development, which students could use inside and outside the classroom. Today’s sophisticated learning tools range from virtual environments to interactive multimedia resources,...
-
Dependable Integration of Medical Image Recognition Components
PublikacjaComputer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....
-
Real-Time Bleeding Detection in Gastrointestinal Tract Endoscopic Examinations Video
PublikacjaThe article presents a novel approach to medical video data analysis and recognition of bleedings. Emphasis has been put on adapting pre-existing algorithms dedicated to the detection of bleedings for real-time usage in a medical doctor’s office during an endoscopic examination. A real-time system for analyzing endoscopic videos has been designed according to the most significant requirements of medical doctors. The main goal of...
-
Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
-
Survival time prognosis under a Markov model of cancer development
PublikacjaIn 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.
-
The data exchange between smart glasses and healthcare information systems using the HL7 FHIR standard
PublikacjaIn this study we evaluated system architecture for the use of smart glasses as a viewer of information, as a source of medical data (vital sign measurements: temperature, pulse rate, and respiration rate), and as a filter of healthcare information. All activities were based on patient/device identification procedures using graphical markers or features based on visual appearance. The architecture and particular use cases were implemented...