Wyniki wyszukiwania dla: machine learning · artficial intelligence · deep learning · small vessels disease · explainable ai · trustworthiness. - MOST Wiedzy

Wyszukiwarka

Wyniki wyszukiwania dla: machine learning · artficial intelligence · deep learning · small vessels disease · explainable ai · trustworthiness.

Wyniki wyszukiwania dla: machine learning · artficial intelligence · deep learning · small vessels disease · explainable ai · trustworthiness.

  • Olgun Aydin dr

    Olgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...

  • Deep Learning

    Publikacja

    - Rok 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Deep Learning: A Case Study for Image Recognition Using Transfer Learning

    Publikacja

    - Rok 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data

    Publikacja

    - IEEE Journal of Translational Engineering in Health and Medicine-JTEHM - Rok 2024

    The field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...

    Pełny tekst do pobrania w portalu

  • Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches

    Publikacja
    • V. G. Nguyen
    • P. Sharma
    • Ü. Ağbulut
    • H. S. Le
    • D. N. Cao
    • M. Dzida
    • S. M. Osman
    • H. C. Le
    • V. D. Tran

    - International Journal of Green Energy - Rok 2024

    Examining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Source code - AI models (MLM1-5 - series I-III - QNM opt)

    Dane Badawcze
    open access

    Source code - AI models (MLM1-5 - series I-III - QNM opt) for the paper "Computational Complexity and Its Influence on Concrete Compressive Strength Prediction Capabilities of Machine Learning Models for Concrete Mix Design Support" accepted for publication.

  • Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks

    Deep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...

    Pełny tekst do pobrania w portalu

  • Machine Learning and Electronic Noses for Medical Diagnostics

    Publikacja

    The need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy

    Publikacja
    • G. V. Nguyen
    • P. Sharma
    • Ü. Ağbulut
    • H. S. Le
    • T. H. Truong
    • M. Dzida
    • M. H. Tran
    • H. C. Le
    • V. D. Tran

    - Biofuels Bioproducts & Biorefining-Biofpr - Rok 2024

    Biochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Predicting emotion from color present in images and video excerpts by machine learning

    Publikacja

    This work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...

    Pełny tekst do pobrania w portalu

  • THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN

    Publikacja

    - Rok 2021

    In 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...

  • Abdalraheem Ijjeh Ph.D. Eng.

    Osoby

    The primary research areas of interest are artificial intelligence (AI), machine learning, deep learning, and computer vision, as well as modeling physical phenomena (i.e., guided waves in composite laminates). The research interests described above are utilized for SHM and NDE applications, namely damage detection and localization in composite materials.  

  • Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects

    Publikacja
    • V. N. N. Nhanh Van
    • W. Tarełko
    • S. Prabhakar
    • A. S. El-Shafay
    • W. Chen
    • P. Q. P. Nguyen
    • N. X. Phuong
    • T. A. Nguyen

    - ENERGY & FUELS - Rok 2024

    Modern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach

    Publikacja

    Breast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...

    Pełny tekst do pobrania w portalu

  • A note on the applications of artificial intelligence in the hospitality industry: preliminary results of a survey

    Publikacja

    - Rok 2021

    Intelligent technologies are widely implemented in different areas of modern society but specific approaches should be applied in services. Basic relationships refer to supporting customers and people responsible for services offering for these customers. The aim of the paper is to analyze and evaluate the state-of-the art of artificial intelligence (AI) applications in the hospitality industry. Our findings show that the major...

    Pełny tekst do pobrania w portalu

  • Book Review

    Acting over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design

    Publikacja

    - Materials - Rok 2023

    The design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...

    Pełny tekst do pobrania w portalu

  • Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2024

    This guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...

    Pełny tekst do pobrania w portalu

  • Data governance: Organizing data for trustworthy Artificial Intelligence

    Publikacja
    • M. Janssen
    • P. Brous
    • E. Estevez
    • L. S. Barbosa
    • T. Janowski

    - GOVERNMENT INFORMATION QUARTERLY - Rok 2020

    The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....

    Pełny tekst do pobrania w portalu

  • Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models

    Publikacja
    • R. Yurt
    • H. Torpi
    • P. Mahouti
    • A. Kizilay
    • S. Kozieł

    - IEEE Access - Rok 2023

    This work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...

    Pełny tekst do pobrania w portalu

  • Smart Knowledge Engineering for Cognitive Systems: A Brief Overview

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2022

    Cognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...

    Pełny tekst do pobrania w portalu

  • University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies

    Publikacja

    - Rok 2021

    Leading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...

    Pełny tekst do pobrania w portalu

  • Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents

    Publikacja
    • S. Donghui
    • L. Zhigang
    • J. Zurada
    • A. Manikas
    • J. Guan
    • P. Weichbroth

    - KNOWLEDGE AND INFORMATION SYSTEMS - Rok 2024

    The construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems

    Publikacja
    • A. Kwaśniewska
    • S. Raghava
    • C. Davila
    • M. Sevenier
    • D. Gamba
    • J. Rumiński

    - Rok 2022

    The rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Pedestrian detection in low-resolution thermal images

    Over one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks

    Publikacja

    - IEEE Access - Rok 2022

    Object detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...

    Pełny tekst do pobrania w portalu

  • Explainable machine learning for diffraction patterns

    Publikacja
    • S. Nawaz
    • V. Rahmani
    • D. Pennicard
    • S. P. R. Setty
    • B. Klaudel
    • H. Graafsma

    - Journal of Applied Crystallography - Rok 2023

    Serial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...

    Pełny tekst do pobrania w portalu

  • Deep Learning Basics 2023/24

    Kursy Online
    • K. Draszawka

    A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

  • Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease

    In this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...

    Pełny tekst do pobrania w portalu

  • Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology

    Publikacja
    • A. Kumar Singh
    • H. M. N. Iqbal
    • N. Cardullo
    • V. Muccilli
    • J. Fernández-Lucas
    • J. Ejbye Schmidt
    • T. Jesionowski
    • M. Bilal

    - INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES - Rok 2023

    Lignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Ireneusz Czarnowski Prof.

    Osoby

    IRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...

  • How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?

    Dane Badawcze
    open access

    The data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...

  • Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?

    Publikacja

    - Rok 2023

    Open Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Deep learning in the fog

    In the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...

    Pełny tekst do pobrania w portalu

  • TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads

    TensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...

    Pełny tekst do pobrania w portalu

  • Raw data of AuAg nanoalloy plasmon resonances used for machine learning method

    Raw data used for machine learning process. UV-vis measurements of AuAg alloyed nanostructures created from thin films. Plasmonic band position dependence on fabrication parameters. Small presentation reviewing achieved structures and their properties.

  • Speech Analytics Based on Machine Learning

    In this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Neural networks and deep learning

    Publikacja

    - Rok 2022

    In this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Deep Learning w Keras

    Kursy Online
    • A. Karpus

    Kurs przeznaczony dla słuchaczy studiów podyplomowych Sztuczna inteligencja i automatyzacja procesów biznesowych w ujęciu praktycznym - edycja biznesowa.

  • How Machine Learning Contributes to Solve Acoustical Problems

    Publikacja
    • M. A. Roch
    • P. Gerstoft
    • B. Kostek
    • Z. Michalopoulou

    - Journal of the Acoustical Society of America - Rok 2021

    Machine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...

    Pełny tekst do pobrania w portalu

  • Assessing the attractiveness of human face based on machine learning

    Publikacja

    The attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...

    Pełny tekst do pobrania w portalu

  • Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions

    Publikacja

    - Polimery w Medycynie - Rok 2024

    Background. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...

    Pełny tekst do pobrania w portalu

  • Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers

    The process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Designing acoustic scattering elements using machine learning methods

    Publikacja

    - Rok 2021

    In the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...

    Pełny tekst do pobrania w portalu

  • Data augmentation for improving deep learning in image classification problem

    Publikacja

    These days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Machine Learning Techniques in Concrete Mix Design

    Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...

    Pełny tekst do pobrania w portalu

  • Introduction to the special issue on machine learning in acoustics

    Publikacja
    • Z. Michalopoulou
    • P. Gerstoft
    • B. Kostek
    • M. A. Roch

    - Journal of the Acoustical Society of America - Rok 2021

    When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...

    Pełny tekst do pobrania w portalu

  • Machine Learning in Multi-Agent Systems using Associative Arrays

    Publikacja

    - PARALLEL COMPUTING - Rok 2018

    In this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...

    Pełny tekst do pobrania w portalu

  • Breast MRI segmentation by deep learning: key gaps and challenges

    Publikacja

    Breast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...

    Pełny tekst do pobrania w portalu

  • Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models

    Breast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...

    Pełny tekst do pobrania w serwisie zewnętrznym