Kontakt:
- email:
- natalia.kowalczyk@pg.edu.pl
Zajmowane stanowiska:
Asystent
- miejsce pracy:
- Katedra Inżynierii Biomedycznej
Budynek A Wydziału Elektroniki, Telekomunikacji i Informatyki, EA 106

Publikacje:
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Publikacja
- T. Kocejko
- T. Neumann
- M. Mazur-Milecka
- N. Kowalczyk
- J. Rumiński
- J. Kang-Hyun
- M. Kaszyński
- T. Ludwisiak
- Rok 2024
This paper introduces a Smart City solution designed to run on edge devices, leveraging NVIDIA's DeepStream SDK for efficient urban surveillance. We evaluate five object-tracking approaches, using YOLO as the baseline detector and integrating three Nvidia DeepStream trackers: IOU, NvSORT, and NvDCF. Additionally, we propose a custom tracker based on Optical Flow and Kalman filtering. The presented approach combines advanced machine...
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Publikacja
Pregnancy in a life of a woman, is an important time that is connected with both physiological and psychological changes. This paper aims at developing a digital twin application that allows to assess mother’s health risk and help to diagnose them. The system presented in this paper includes models for three health outcomes: maternal health risk level, diagnosis of gestational diabetes mellitus (GDM), and diagnosis of late onset...
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Publikacja
- M. Mazur-Milecka
- N. Kowalczyk
- K. Jaguszewska
- D. Zamkowska
- D. Wójcik
- K. Preis
- H. Skov
- S. R. Wagner
- P. Sandager
- M. Sobotka
- J. Rumiński
- Rok 2024
This paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Publikacja
The paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Publikacja
- IEEE Access - Rok 2023
Face masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
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