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Search results for: ANNOTATION MEDICAL DATA, CROWD-SOURCING
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublicationDeployment 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...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods 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...
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Medical Image Dataset Annotation Service (MIDAS)
PublicationMIDAS (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...
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Using Synchronously Registered Biosignals Dataset for Teaching Basics of Medical Data Analysis – Case Study
PublicationMedical 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...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn 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...
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Interaction with medical data using QR-codes
PublicationBar-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....
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Data processing methods for dynamic medical thermography.
PublicationArtykuł 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.
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Scientific tools for collecting and analysing medical data in rhinology.
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Chest Injuries Based on Medical Rescue Team Data
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A survey of medical researchers indicates poor awareness of research data management processes and a role for data librarians
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Improving medical experts’ efficiency of misinformation detection: an exploratory study
PublicationFighting 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...
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Focus on Misinformation: Improving Medical Experts’ Efficiency of Misinformation Detection
PublicationFighting 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...
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Technical Engine for Democratization of Modeling, Simulations, and Predictions
PublicationComputational 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...
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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublicationA 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...
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Semantic segmentation training using imperfect annotations and loss masking
PublicationOne 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...
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Towards Healthcare Cloud Computing
PublicationIn 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...
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Active Learning Based on Crowdsourced Data
PublicationThe 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...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-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...
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Framework for Integration Decentralized and Untrusted Multi-vendor IoMT Environments
PublicationLack 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...
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Polyurethanes as a Potential Medical-Grade Filament for Use in Fused Deposition Modeling 3D Printers – a Brief Review
PublicationThe 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...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublicationIn 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...
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A new approach to modeling of selected human respiratory system diseases, directed to computer simulations
PublicationThis 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...
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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...
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Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
PublicationML 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...
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Proposal of a Mobile Medical Waste Incinerator with Application of Automatic Waste Feeder and Heat Recovery System as a Novelty in Poland
PublicationThe 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....
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Analysis-by-synthesis paradigm evolved into a new concept
PublicationThis 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...
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Data Mining Applications and Methods in Medicine
PublicationIn 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....
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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
PublicationThe 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...
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Proposal of a mobile medical waste incinerator with automatic waste feeder and heat recovery system
PublicationThe 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,...
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A comprehensive evaluation of flexible FDM/FFF 3D printing filament as a potential material in medical application
PublicationThe 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...
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Platforma IPMed jako elastyczne źródło danych dla medycznych zespołów naukowych
PublicationPrzedstawiono 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.
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ANYTIME POLYNOMIAL HEURISTIC ALGORITHM FOR PARTITIONING GROUPS OF DATA WITH PRESERVING CLASS PROPORTIONS FOR CROSS-VALIDATION
PublicationThe 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...
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Multichannel Human Body Communication
PublicationHuman 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...
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The design of an intelligent medical space supporting automated patient interviewing
PublicationThe 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...
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Online Interactivity – Shift Towards E-textbook-based Medical Education
PublicationTextbooks 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,...
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Dependable Integration of Medical Image Recognition Components
PublicationComputer 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....
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Real-Time Bleeding Detection in Gastrointestinal Tract Endoscopic Examinations Video
PublicationThe 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...
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Application of autoencoder to traffic noise analysis
PublicationThe 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...
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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.
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The data exchange between smart glasses and healthcare information systems using the HL7 FHIR standard
PublicationIn 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...
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Active IR-Thermal Imaging in Medicine
PublicationIn this paper we summarize results of several research projects devoted to development of new diagnostic methods and procedures based on quantitative infrared thermography in medical applications. First, basics of active dynamic thermography are presented. Described are both, instrumentation and software comprising measurement procedures including collection of series of IR-images after external excitation, data treatment with...
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Active Dynamic Thermography in Medical Diagnostics
PublicationThis is an overview of active thermal imaging methods in medical diagnostics using external thermal stimulation. In this chapter, several clinical cases diagnosed using the active dynamic thermography method, ADT, are presented. Features of this technology are discussed and main advantages underlined. Applications in skin burn diagnostics and quantitative evaluation leading to modern classification of burned patients for further...
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Qualitative evaluation of distributed clinical systems supporting research teams working on large-scale data
PublicationInthispaper,fivecontemporaryscalablesystemstosupportmedicalresearchteams are presented. Their functionalities extend from heterogeneous unstructured data acquisition through large-scale data storing, to on-the-fly analyzing by using robust methods. Such kinds of systems can be useful in the development of new medical procedures and recommendation rules for decision support systems. A short description of each of them is provided....
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Cluster donation: How medical students bound certain types of tissues and biomedical research and how it affects their willingness to donate.
PublicationAlthough biomedical research requires cooperation with a large number of donors, its success also depends on the input of healthcare professionals who play a crucial role in promoting biomedical research and influencing an individual’s decision to donate one’s biospecimens that are left over after a medical procedure. This work was aimed at investigating the correlation between medical and healthcare students’ willingness to...
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To donate or not to donate? Future healthcare professionals’ opinions on biobanking of human biological material for research purposes
PublicationBackground Over the last few decades biobanks have been recognised as institutions that may revolutionisebiomedical research and the development of personalised medicine. Poland, however, still lacks clear regulationsregarding the running of biobanks and the conducting of biomedical research. While the awareness of the generalpublic regarding biobanks is low, healthcare professions and medical students also...
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Supporting compliance with safety standards by trust case templates
PublicationStandard Compliance (SC) Framework presented in this paper encompasses methods and tools which provide support for application of standards. The framework is based on trust case methodology. A trust case is a data structure which represents a justification that an object (a system, an infrastructure, an organization) exhibits certain properties. It contains an argument and related evidence which support claimed properties. A trust...
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Detection of gaseous compounds with different techniques
PublicationSensing technology has been developed for detection of gases in some environmental, industrial, medical, and scientific applications. The main tasks of these works is to enhance performance of gas sensors taking into account their different applicability and scenarios of operation. This paper presents the descriptions, comparison and recent progress in some existing gas sensing technologies. Detailed introduction to optical sensing...
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Investigating beliefs in anti-vax conspiracy theories among medical students
PublicationAbstract: While the doctors’ role in immunization is essential, their lack of knowledge or vaccine hesitancy may affect their ability to communicate effectively and educate patients about vaccination, vaccine hesitancy, and vaccine conspiracy theories. This, in turn, may hinder health policy aimed at fighting infectious diseases. Vaccine hesitancy is prevalent not only among the general population but also among healthcare...
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Multi-agent large-scale parallel crowd simulation
PublicationThis paper presents design, implementation and performance results of a new modular, parallel, agent-based and large scale crowd simulation environment. A parallel application, implemented with C and MPI, was implemented and run in this parallel environment for simulation and visualization of an evacuation scenario at Gdansk University of Technology, Poland and further in the area of districts of Gdansk. The application uses a...
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Digital Photogrammetry in the Analysis of the Ventricles' Shape and Size
PublicationThis article presents spatial analyzes conducted to assess the potential of ReMake software to be used for medical purposes, with emphasis on the analysis of the shape and dimensions of the ventricles. To achieve this goal, the length of the sections measured with the ReMake and Image Master programs have been compared. RMS error was on the level of 1.2 mm. In addition to indicating the appropriateness of using this software, there...