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302 results on '"Suwalska, Aleksandra"'

1. Role of Assistive Robots in the Care of Older People: Survey Study Among Medical and Nursing Students

Author

Łukasik, Sylwia, Tobis, Sławomir, Kropińska, Sylwia, and Suwalska, Aleksandra

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundPopulations are aging at an alarming rate in many countries around the world. There has been not only a decrease in the number of births and an increase in the percentage of older people, but also an increase in the number of people living alone. There is growing demand for specialist medical care and daily care with the number of people who can act as caregivers reducing. The use of assistive robots can, at least partially, solve these problems. ObjectiveThe purpose of this study was to examine the opinions of future health care professionals (medical and nursing students) regarding the use of assistive robots in the care of older people. MethodsThe study was conducted with a group of 178 students from Poznan University of Medical Sciences, Poznań, Poland (110 nursing students and 68 medical students), using the Users’ Needs, Requirements, and Abilities Questionnaire. ResultsThe participants of this study believed that assistive robots should, first of all, remind older people to take medication regularly, ensure their safety, monitor their health status and environment, provide cognitive training, and encourage them to maintain physical activity. In the students’ opinion, the robot should not be an older person’s companion but only act as an assistant. Nursing students had significantly higher scores than medical students in several statements concerning everyday use of robots, including reminding about meals (P=.03), monitoring the environment (P=.001), providing advice about a healthy diet (P=.04), monitoring the intake of food and fluids (P=.02), and automatic “switch on” function (P=.02). Nursing students were more focused on the social functions of robots, including encouraging contact with friends (P=.003) and reducing the sense of loneliness and improving mood (P=.008). Medical students were more aware of privacy issues in the statement concerning the possibility of switching off the robot in specific situations (P=.01). ConclusionsOur study revealed a generally positive attitude of future doctors and nurses toward assistive robots, which can have an impact on their acceptance by older adults. In the future, medical professionals could help their patients to choose the right robots (and necessary functions) that are best suited to their needs. However, this would require expanding the curriculum to include the issues of gerontechnology.

Published
2020
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2. Combining low-dose CT-based radiomics and metabolomics for early lung cancer screening support

Author

Zyla, Joanna, Marczyk, Michal, Prazuch, Wojciech, Socha, Marek, Suwalska, Aleksandra, Durawa, Agata, Jelitto-Gorska, Malgorzata, Dziadziuszko, Katarzyna, Szurowska, Edyta, Rzyman, Witold, Widlak, Piotr, and Polanska, Joanna

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Statistics - Applications
Abstract

Due to its predominantly asymptomatic or mildly symptomatic progression, lung cancer is often diagnosed in advanced stages, resulting in poorer survival rates for patients. As with other cancers, early detection significantly improves the chances of successful treatment. Early diagnosis can be facilitated through screening programs designed to detect lung tissue tumors when they are still small, typically around 3mm in size. However, the analysis of extensive screening program data is hampered by limited access to medical experts. In this study, we developed a procedure for identifying potential malignant neoplastic lesions within lung parenchyma. The system leverages machine learning (ML) techniques applied to two types of measurements: low-dose Computed Tomography-based radiomics and metabolomics. Using data from two Polish screening programs, two ML algorithms were tested, along with various integration methods, to create a final model that combines both modalities to support lung cancer screening.

Published
2023

3. BRONCO: Automated modelling of the bronchovascular bundle using the Computed Tomography Images

Author

Prażuch, Wojciech, Socha, Marek, Mrukwa, Anna, Suwalska, Aleksandra, Durawa, Agata, Jelitto-Górska, Malgorzata, Dziadziuszko, Katarzyna, Szurowska, Edyta, Bożek, Pawel, Marczyk, Michal, Rzyman, Witold, and Polanska, Joanna

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Segmentation of the bronchovascular bundle within the lung parenchyma is a key step for the proper analysis and planning of many pulmonary diseases. It might also be considered the preprocessing step when the goal is to segment the nodules from the lung parenchyma. We propose a segmentation pipeline for the bronchovascular bundle based on the Computed Tomography images, returning either binary or labelled masks of vessels and bronchi situated in the lung parenchyma. The method consists of two modules, modeling of the bronchial tree and vessels. The core revolves around a similar pipeline, the determination of the initial perimeter by the GMM method, skeletonization, and hierarchical analysis of the created graph. We tested our method on both low-dose CT and standard-dose CT, with various pathologies, reconstructed with various slice thicknesses, and acquired from various machines. We conclude that the method is invariant with respect to the origin and parameters of the CT series. Our pipeline is best suited for studies with healthy patients, patients with lung nodules, and patients with emphysema.

Published
2023

4. POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021)

Author

Suwalska, Aleksandra, Tobiasz, Joanna, Prazuch, Wojciech, Socha, Marek, Foszner, Pawel, Piotrowski, Damian, Gruszczynska, Katarzyna, Sliwinska, Magdalena, Walecki, Jerzy, Popiela, Tadeusz, Przybylski, Grzegorz, Nowak, Mateusz, Fiedor, Piotr, Pawlowska, Malgorzata, Flisiak, Robert, Simon, Krzysztof, Zapolska, Gabriela, Gizycka, Barbara, Szurowska, Edyta, Group, POLCOVID Study, Marczyk, Michal, Cieszanowski, Andrzej, and Polanska, Joanna

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, I.4.6, I.4.9
Abstract

The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and required medical assistance. With chest radiographs (CXR) being one of the most common COVID-19 diagnosis methods, many artificial intelligence tools for image-based COVID-19 detection have been developed, often trained on a small number of images from COVID-19-positive patients. Thus, the need for high-quality and well-annotated CXR image databases increased. This paper introduces POLCOVID dataset, containing chest X-ray (CXR) images of patients with COVID-19 or other-type pneumonia, and healthy individuals gathered from 15 Polish hospitals. The original radiographs are accompanied by the preprocessed images limited to the lung area and the corresponding lung masks obtained with the segmentation model. Moreover, the manually created lung masks are provided for a part of POLCOVID dataset and the other four publicly available CXR image collections. POLCOVID dataset can help in pneumonia or COVID-19 diagnosis, while the set of matched images and lung masks may serve for the development of lung segmentation solutions., Comment: 13 pages, 3 figures

Published
2022

5. CIRCA: comprehensible online system in support of chest X-rays-based COVID-19 diagnosis

Author

Prazuch, Wojciech, Suwalska, Aleksandra, Socha, Marek, Tobiasz, Joanna, Foszner, Pawel, Jaroszewicz, Jerzy, Gruszczynska, Katarzyna, Sliwinska, Magdalena, Walecki, Jerzy, Popiela, Tadeusz, Przybylski, Grzegorz, Cieszanowski, Andrzej, Nowak, Mateusz, Pawlowska, Malgorzata, Flisiak, Robert, Simon, Krzysztof, Zapolska, Gabriela, Gizycka, Barbara, Szurowska, Edyta, Group, POLCOVID Study, Marczyk, Michal, and Polanska, Joanna

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Due to the large accumulation of patients requiring hospitalization, the COVID-19 pandemic disease caused a high overload of health systems, even in developed countries. Deep learning techniques based on medical imaging data can help in the faster detection of COVID-19 cases and monitoring of disease progression. Regardless of the numerous proposed solutions for lung X-rays, none of them is a product that can be used in the clinic. Five different datasets (POLCOVID, AIforCOVID, COVIDx, NIH, and artificially generated data) were used to construct a representative dataset of 23 799 CXRs for model training; 1 050 images were used as a hold-out test set, and 44 247 as independent test set (BIMCV database). A U-Net-based model was developed to identify a clinically relevant region of the CXR. Each image class (normal, pneumonia, and COVID-19) was divided into 3 subtypes using a 2D Gaussian mixture model. A decision tree was used to aggregate predictions from the InceptionV3 network based on processed CXRs and a dense neural network on radiomic features. The lung segmentation model gave the Sorensen-Dice coefficient of 94.86% in the validation dataset, and 93.36% in the testing dataset. In 5-fold cross-validation, the accuracy for all classes ranged from 91% to 93%, keeping slightly higher specificity than sensitivity and NPV than PPV. In the hold-out test set, the balanced accuracy ranged between 68% and 100%. The highest performance was obtained for the subtypes N1, P1, and C1. A similar performance was obtained on the independent dataset for normal and COVID-19 class subtypes. Seventy-six percent of COVID-19 patients wrongly classified as normal cases were annotated by radiologists as with no signs of disease. Finally, we developed the online service (https://circa.aei.polsl.pl) to provide access to fast diagnosis support tools.

Published
2022

7. Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis

Author

Socha, Marek, Prażuch, Wojciech, Suwalska, Aleksandra, Foszner, Paweł, Tobiasz, Joanna, Jaroszewicz, Jerzy, Gruszczynska, Katarzyna, Sliwinska, Magdalena, Nowak, Mateusz, Gizycka, Barbara, Zapolska, Gabriela, Popiela, Tadeusz, Przybylski, Grzegorz, Fiedor, Piotr, Pawlowska, Malgorzata, Flisiak, Robert, Simon, Krzysztof, Walecki, Jerzy, Cieszanowski, Andrzej, Szurowska, Edyta, Marczyk, Michal, and Polanska, Joanna

Published
2023
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8. Comparison of Batch Effect Removal Methods for High Dimensional Mass Cytometry Data

Author

Suwalska, Aleksandra, du Plessis-Burger, Nelita, van der Spuy, Gian, Polanska, Joanna, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Rojas, Ignacio, editor, Valenzuela, Olga, editor, Rojas, Fernando, editor, Herrera, Luis Javier, editor, and Ortuño, Francisco, editor

Published
2022
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12. Psychosocial and cultural determinants of dietary intake in community-dwelling older adults: A Determinants of Diet and Physical Activity systematic literature review

Author

Poggiogalle, Eleonora, Kiesswetter, Eva, Romano, Mariagrazia, Saba, Anna, Sinesio, Fiorella, Polito, Angela, Moneta, Elisabetta, Ciarapica, Donatella, Migliaccio, Silvia, Suwalska, Aleksandra, Wieczorowska-Tobis, Katarzyna, Pałys, Wiktor, Łojko, Dorota, Sulmont-Rossé, Claire, Feart, Catherine, Brug, Johannes, Volkert, Dorothee, and Donini, Lorenzo M.

Published
2021
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14. Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder

Author

Nunes, Abraham, Stone, William, Ardau, Raffaella, Berghöfer, Anne, Bocchetta, Alberto, Chillotti, Caterina, Deiana, Valeria, Degenhardt, Franziska, Forstner, Andreas J., Garnham, Julie S., Grof, Eva, Hajek, Tomas, Manchia, Mirko, Mattheisen, Manuel, McMahon, Francis, Müller-Oerlinghausen, Bruno, Nöthen, Markus M., Pinna, Marco, Pisanu, Claudia, O’Donovan, Claire, Rietschel, Marcella D. C., Rouleau, Guy, Schulze, Thomas, Severino, Giovanni, Slaney, Claire M., Squassina, Alessio, Suwalska, Aleksandra, Turecki, Gustavo, Uher, Rudolf, Zvolsky, Petr, Cervantes, Pablo, del Zompo, Maria, Grof, Paul, Rybakowski, Janusz, Tondo, Leonardo, Trappenberg, Thomas, and Alda, Martin

Published
2021
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20. The EnrichMe Project : A Robotic Solution for Independence and Active Aging of Elderly People with MCI

Author

Salatino, Claudia, Gower, Valerio, Ghrissi, Meftah, Tapus, Adriana, Wieczorowska-Tobis, Katarzyna, Suwalska, Aleksandra, Barattini, Paolo, Rosso, Roberto, Munaro, Giulia, Bellotto, Nicola, van den Heuvel, Herjan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Miesenberger, Klaus, editor, Bühler, Christian, editor, and Penaz, Petr, editor

Published
2016
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23. Internet use by patients with bipolar disorder: Results from an international multisite survey

Author

Bauer, Rita, Conell, Jörn, Glenn, Tasha, Alda, Martin, Ardau, Raffaella, Baune, Bernhard T., Berk, Michael, Bersudsky, Yuly, Bilderbeck, Amy, Bocchetta, Alberto, Bossini, Letizia, Castro, Angela M. Paredes, Cheung, Eric YW., Chillotti, Caterina, Choppin, Sabine, Del Zompo, Maria, Dias, Rodrigo, Dodd, Seetal, Duffy, Anne, Etain, Bruno, Fagiolini, Andrea, Hernandez, Miryam Fernández, Garnham, Julie, Geddes, John, Gildebro, Jonas, Gonzalez-Pinto, Ana, Goodwin, Guy M., Grof, Paul, Harima, Hirohiko, Hassel, Stefanie, Henry, Chantal, Hidalgo-Mazzei, Diego, Kapur, Vaisnvy, Kunigiri, Girish, Lafer, Beny, Larsen, Erik R., Lewitzka, Ute, Licht, Rasmus W., Lund, Anne Hvenegaard, Misiak, Blazej, Monteith, Scott, Munoz, Rodrigo, Nakanotani, Takako, Nielsen, René E, O’Donovan, Claire, Okamura, Yasushi, Osher, Yamima, Piotrowski, Patryk, Reif, Andreas, Ritter, Philipp, Rybakowski, Janusz K., Sagduyu, Kemal, Sawchuk, Brett, Schwartz, Elon, Scippa, Ângela M., Slaney, Claire, Sulaiman, Ahmad H., Suominen, Kirsi, Suwalska, Aleksandra, Tam, Peter, Tatebayashi, Yoshitaka, Tondo, Leonardo, Vieta, Eduard, Vinberg, Maj, Viswanath, Biju, Volkert, Julia, Zetin, Mark, Whybrow, Peter C., and Bauer, Michael

Published
2016
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25. Postępy w onkologii obliczeniowej i spersonalizowanej medycynie. T. 2, Wyzwania przyszłości

Author

Adamiec-Organiściok, Małgorzata, Bartnicka, Joanna, Bernyś, Michał, Białecki, Ryszard, Bojar, Piotr, Borys, Damian, Bugdol, Monika, Choiński, Dariusz, Frąckiewicz, Mariusz, Gil, Jarosław, Głowacki, Jan, Gogler-Pigłowska, Agnieszka, Gracka, Maria, Herrera, Cristina, Hudecki, Andrzej, Hybiak, Jolanta, Jankowska, Kornelia, Jędrzejowski, Maksymilian, Juszczyk, Jan, Kabiesz, Patrycja, Kalisz, Seweryn, Kania, Mateusz, Kipsang, Benard, Kostka, Daria, Kowol, Karolina, Krukiewicz, Katarzyna, Langer-Macioł, Hanna, Lucińska, Kinga, Łos, Marek J., Majchrzak, Ewa, Marczyk, Michał, Melka, Bartłomiej, Mleczko, Katarzyna, Ostrowski, Ziemowit, Patel, Taral, Peters, Harm, Piętka, Ewa, Płonka, Wiktoria, Polańska, Joanna, Polański, Andrzej, Prażuch, Wojciech, Psiuk-Maksymowicz, Krzysztof, Pyciński, Bartłomiej, Rojczyk, Marek, Rutto, Wesley Chebii, San Martin Valenzuela, Constanza, Sieradzka, Katarzyna, Sikora, Wojciech, Skonieczna, Magdalena, Skorupa, Małgorzata, Skupin, Piotr, Socha, Marek, Sojka, Damian, Staśczak, Alicja, Strózik, Barbara, Student, Sebastian, Suwalska, Aleksandra, Szymiczek, Krzysztof, Ścieglińska, Dorota, Śliwińska, Wiktoria, Tobiasz, Joanna, Wasilewski, Jarosław, Wencel, Przemysław, Widzisz, Karolina, Wilczek, Piotr, Ziętkiewicz, Agnieszka, POLCOVID Study Group, Krukiewicz, Katarzyna. Red., Marczyk, Michał. Red., Bugdol, Monika. Red., Bajkacz, Sylwia. Red., Ostrowski, Ziemowit. Red., and Polańska, Joanna. Red. serii

Subjects
bioinformatyka, onkologia obliczeniowa, medycyna spersonalizowana, modelowanie numeryczne, e-learning, biomateriały
Published
2023
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27. POLCOVID : a multicenter multiclass chest X-ray database (Poland, 2020–2021)

Author

Suwalska, Aleksandra, Tobiasz, Joanna, Prazuch, Wojciech, Socha, Marek, Foszner, Pawel, Piotrowski, Damian, Gruszczynska, Katarzyna, Sliwinska, Magdalena, Walecki, Jerzy, Popiela, Tadeusz, Przybylski, Grzegorz, Nowak, Mateusz, Fiedor, Piotr, Pawlowska, Malgorzata, Flisiak, Robert, Simon, Krzysztof, Zapolska, Gabriela, Gizycka, Barbara, Szurowska, Edyta, Marczyk, Michal, Cieszanowski, Andrzej, and Polanska, Joanna

Published
2023

28. Studies on candidate genes for lithium prophylaxis performed at the Poznan University of Medical Sciences

Author

Ferensztajn-Rochowiak, Ewa, primary, Dmitrzak-Węglarz, Monika, additional, Szczepankiewicz, Aleksandra, additional, Skibińska, Maria, additional, Kliwicki, Sebastian, additional, Permoda-Pachuta, Agnieszka, additional, Suwalska, Aleksandra, additional, Czerski, Piotr, additional, Pawlak, Joanna, additional, and Hauser, Joanna, additional

Published
2022
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30. Diet and physical activity and metabolic disorders in patients with schizophrenia and bipolar affective disorder in the Polish population.

Author

Głodek, Magdalena, Skibinska, Maria, and Suwalska, Aleksandra

Subjects
PHYSICAL activity, POLISH people, METABOLIC disorders, PEOPLE with schizophrenia, AFFECTIVE disorders, GHRELIN, ADIPOKINES
Abstract

Introduction: There are numerous reports of a higher prevalence of metabolic disorders in patients with schizophrenia and bipolar disorder (BD), yet its connections to diet and physical activity remain not fully explained. This article aimed to evaluate diet, physical activity and selected biochemical and anthropometric parameters associated with metabolism in patients with schizophrenia and BD and to analyse the relationships between these variables in the subjects. Materials and Methods: A total of 126 adults participated in the study: 47 patients with schizophrenia, 54 patients with BD and 25 patients in mental illness remission (reference group). Data were collected on the underlying illness and concomitant illnesses, and the severity of symptoms of the current episode was assessed using the following scales: PANSS, MADRS and YMRS. An assessment of the subjects' diet (KomPAN questionnaire) and their physical activity (International Physical Activity Questionnaire) was carried out. Anthropometric and blood pressure measurements were taken and BMI and WHR were calculated. Serum concentrations of fasting glucose, TSH, total cholesterol, LDL and HDL fractions, triglycerides and leptin, ghrelin and resistin were determined. For statistical analysis, the significance level was set at 0.05. For multiple comparisons one way ANOVA or Kruskal Wallis were used with post hoc Tukey and Dunn tests, respectively. To determine correlation of variables, Pearson's linear correlation coefficient or Spearman's rank correlation coefficient were used. Results: A total of 50.8% of the subjects had at least one metabolic disorder--most commonly excessive body weight (66.7%) and abdominal obesity (64.3%). Patients did not differ significantly in terms of physical activity, but they did differ in mean time spent sitting--with this being significantly longer for all groups than in the general population. The subjects differed in diet: patients with BD consumed less unhealthy foods than patients with schizophrenia. The highest correlations between physical activity, diet and variables defining metabolic disorders were found in patients with BD. Only in patients with schizophrenia were there significant correlations between the course of the disease and physical activity. Discussion: The results suggest the existence of associations between diet, physical activity, and metabolic disorders in both BD and schizophrenia patients. They also suggest a tendency among those patients to spend long periods of time sitting. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Internet use by older adults with bipolar disorder: international survey results

Author

Bauer, Rita, Glenn, Tasha, Strejilevich, Sergio, Conell, Jörn, Alda, Martin, Ardau, Raffaella, Baune, Bernhard T., Berk, Michael, Bersudsky, Yuly, Bilderbeck, Amy, Bocchetta, Alberto, Castro, Angela M. Paredes, Cheung, Eric Y. W., Chillotti, Caterina, Choppin, Sabine, Cuomo, Alessandro, Del Zompo, Maria, Dias, Rodrigo, Dodd, Seetal, Duffy, Anne, Etain, Bruno, Fagiolini, Andrea, Fernández Hernandez, Miryam, Garnham, Julie, Geddes, John, Gildebro, Jonas, Gitlin, Michael J., Gonzalez-Pinto, Ana, Goodwin, Guy M., Grof, Paul, Harima, Hirohiko, Hassel, Stefanie, Henry, Chantal, Hidalgo-Mazzei, Diego, Lund, Anne Hvenegaard, Kapur, Vaisnvy, Kunigiri, Girish, Lafer, Beny, Larsen, Erik R., Lewitzka, Ute, Licht, Rasmus W., Misiak, Blazej, Piotrowski, Patryk, Miranda-Scippa, Ângela, Monteith, Scott, Munoz, Rodrigo, Nakanotani, Takako, Nielsen, René E., O’Donovan, Claire, Okamura, Yasushi, Osher, Yamima, Reif, Andreas, Ritter, Philipp, Rybakowski, Janusz K., Sagduyu, Kemal, Sawchuk, Brett, Schwartz, Elon, Slaney, Claire, Sulaiman, Ahmad H., Suominen, Kirsi, Suwalska, Aleksandra, Tam, Peter, Tatebayashi, Yoshitaka, Tondo, Leonardo, Veeh, Julia, Vieta, Eduard, Vinberg, Maj, Viswanath, Biju, Zetin, Mark, Whybrow, Peter C., and Bauer, Michael

Published
2018
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32. Online information seeking by patients with bipolar disorder: results from an international multisite survey

Author

Conell, Jörn, Bauer, Rita, Glenn, Tasha, Alda, Martin, Ardau, Raffaella, Baune, Bernhard T., Berk, Michael, Bersudsky, Yuly, Bilderbeck, Amy, Bocchetta, Alberto, Bossini, Letizia, Paredes Castro, Angela Marianne, Cheung, Eric Yat Wo, Chillotti, Caterina, Choppin, Sabine, Del Zompo, Maria, Dias, Rodrigo, Dodd, Seetal, Duffy, Anne, Etain, Bruno, Fagiolini, Andrea, Garnham, Julie, Geddes, John, Gildebro, Jonas, Gonzalez-Pinto, Ana, Goodwin, Guy M., Grof, Paul, Harima, Hirohiko, Hassel, Stefanie, Henry, Chantal, Hidalgo-Mazzei, Diego, Kapur, Vaisnvy, Kunigiri, Girish, Lafer, Beny, Lam, Chun, Larsen, Erik Roj, Lewitzka, Ute, Licht, Rasmus, Lund, Anne Hvenegaard, Misiak, Blazej, Piotrowski, Patryk, Monteith, Scott, Munoz, Rodrigo, Nakanotani, Takako, Nielsen, René E., O’Donovan, Claire, Okamura, Yasushi, Osher, Yamima, Reif, Andreas, Ritter, Philipp, Rybakowski, Janusz K., Sagduyu, Kemal, Sawchuk, Brett, Schwartz, Elon, Scippa, Ângela Miranda, Slaney, Claire, Sulaiman, Ahmad Hatim, Suominen, Kirsi, Suwalska, Aleksandra, Tam, Peter, Tatebayashi, Yoshitaka, Tondo, Leonardo, Vieta, Eduard, Vinberg, Maj, Viswanath, Biju, Volkert, Julia, Zetin, Mark, Zorrilla, Iñaki, Whybrow, Peter C., and Bauer, Michael

Published
2016
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36. The EnrichMe Project

Author

Salatino, Claudia, primary, Gower, Valerio, additional, Ghrissi, Meftah, additional, Tapus, Adriana, additional, Wieczorowska-Tobis, Katarzyna, additional, Suwalska, Aleksandra, additional, Barattini, Paolo, additional, Rosso, Roberto, additional, Munaro, Giulia, additional, Bellotto, Nicola, additional, and van den Heuvel, Herjan, additional

Published
2016
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37. nUMAP: rozwiązanie dla wizualizacji wielu zbiorów danych oparte na sieciach neuronowych

Author

Suwalska, Aleksandra, Socha, Marek, Prażuch, Wojciech, Tobiasz, Joanna, Polańska, Joanna, Marczyk, Michał, POLCOVID Study Group, Krukiewicz, Katarzyna. Red., Bajkacz, Sylwia. Red., Marczyk, Michał. Red., Ostrowski, Ziemowit. Red., Bugdol, Monika. Red., and Polańska, Joanna. Red. serii

Subjects
Big Data, onkologia obliczeniowa, standard UMAP, UMAP (Uniform Manifold Approximation and Projection), wizualizacja, zbiory danych, medycyna spersonalizowana, sieci neuronowe
Published
2022

38. Influence of various preprocessing techniques and model parameters on network performance in COVID-19 detection

Author

Śliwińska, Wiktoria, Suwalska, Aleksandra, Marczyk, Michał, Krukiewicz, Katarzyna. Red., Bajkacz, Sylwia. Red., Marczyk, Michał. Red., Ostrowski, Ziemowit. Red., Bugdol, Monika. Red., and Polańska, Joanna. Red. serii

Subjects
głębokie uczenie maszynowe, onkologia obliczeniowa, klasyfikacja obrazów, Deep Learning, badania RTG, obrazy radiologiczne, przetwarzanie danych obrazowych, COVID-19, diagnostyka medyczna, medycyna spersonalizowana
Published
2022

39. Graficzna reprezentacja heterogenicznosci zbioru radiogramów z bazy POLCOVID za pomocą techniki UMAP

Author

Prażuch, Wojciech, Socha, Marek, Suwalska, Aleksandra, Marczyk, Michał, Polańska, Joanna, POLCOVID Study Group, Bajkacz, Sylwia. Red., Ostrowski, Ziemowit. Red., and Polańska, Joanna. Red. serii

Subjects
onkologia obliczeniowa, badania RTG, obrazy radiologiczne, COVID-19, diagnostyka obrazowa, Uniform Manifold Approximation and Projection (UMAP), RTG klatki piersiowej, medycyna spersonalizowana, technika UMAP, radiomika
Published
2022
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40. Recent advances in computational oncology and personalized medicine. Vol. 1, Here and now!

Author

Bartnicka, Joanna, Prażuch, Wojciech, Bobek, Jarosław, Deorowicz, Sebastian, Długosz, Maciej, Dylong, Mariola, Foszner, Paweł, Garbowska, Iga, Gładys, Bartłomiej, Gorzkowska, Agnieszka, Hermansa, Marek, Hoeftmann, Magdalena, Hudecki, Andrzej, Hybiak, Jolanta, Jaksik, Roman, Jankowska, Kornelia, Jastrząb, Tomasz, Jóźwik-Wabik, Piotr, Jurkojć, Jacek, Kalisz, Seweryn, Kimmel, Marek, Kokot, Marek, Kręcichwost, Michał, Kuś, Paweł, Latos, Magdalena, Łopata, Karolina, Łos, Marek J., Macha, Dawid, Majchrzak, Ewa, Marczyk, Michał, Moćko, Natalia, Molik, Karolina, Pendziałek, Paweł, Piasecka-Belkhayat, Alicja, Polańska, Joanna, Popowicz, Adam, Polański, Andrzej, Różycka, Jagoda, Sage, Agata, Salinger, Julia, Skorupa, Anna, Siwek, Sławomir, Socha, Marek, Stryczyński, Mikołaj, Strzoda, Tomasz, Suwalska, Aleksandra, Szema, Aleksandra, Twardzik, Justyna, Więcławek, Wojciech, Wodarski, Piotr, Zdanowska, Iga, Żak, Weronika, and POLCOVID Study Group

Subjects
bioinformatyka, rehabilitacja, neurologia, angiografia, biotechnologia medyczna, biomechanika, medycyna precyzyjna, przetwarzanie obrazów medycznych, medycyna spersonalizowana, obrazowanie medyczne, inżynieria biomedyczna, onkologia obliczeniowa, biomateriały w medycynie, radiografia, diagnostyka medyczna, informatyka obrazowania, onkologia, rentgenografia
Published
2022
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44. Long-Term Survival of Older Patients Hospitalized for COVID-19. Do Clinical Characteristics upon Admission Matter?

Author

Chojnicki, Michał, primary, Neumann-Podczaska, Agnieszka, additional, Seostianin, Mikołaj, additional, Tomczak, Zofia, additional, Tariq, Hamza, additional, Chudek, Jerzy, additional, Tobis, Sławomir, additional, Mozer-Lisewska, Iwona, additional, Suwalska, Aleksandra, additional, Tykarski, Andrzej, additional, Merks, Piotr, additional, Kropińska, Sylwia, additional, Sobieszczańska, Małgorzata, additional, Romanelli, Frank, additional, and Wieczorowska-Tobis, Katarzyna, additional

Published
2021
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45. Erratum to: Online information seeking by patients with bipolar disorder: results from an international multisite survey

Author

Conell, Jörn, Bauer, Rita, Glenn, Tasha, Alda, Martin, Ardau, Raffaella, Baune, Bernhard T., Berk, Michael, Bersudsky, Yuly, Bilderbeck, Amy, Bocchetta, Alberto, Bossini, Letizia, Paredes Castro, Angela Marianne, Cheung, Eric Yat Wo, Chillotti, Caterina, Choppin, Sabine, Del Zompo, Maria, Dias, Rodrigo, Dodd, Seetal, Duffy, Anne, Etain, Bruno, Fagiolini, Andrea, Garnham, Julie, Geddes, John, Gildebro, Jonas, Gonzalez-Pinto, Ana, Goodwin, Guy M., Grof, Paul, Harima, Hirohiko, Hassel, Stefanie, Henry, Chantal, Hidalgo-Mazzei, Diego, Kapur, Vaisnvy, Kunigiri, Girish, Lafer, Beny, Lam, Chun, Larsen, Erik Roj, Lewitzka, Ute, Licht, Rasmus W., Lund, Anne Hvenegaard, Misiak, Blazej, Piotrowski, Patryk, Monteith, Scott, Munoz, Rodrigo, Nakanotani, Takako, Nielsen, René E., O’Donovan, Claire, Okamura, Yasushi, Osher, Yamima, Reif, Andreas, Ritter, Philipp, Rybakowski, Janusz K., Sagduyu, Kemal, Sawchuk, Brett, Schwartz, Elon, Scippa, Ângela Miranda, Slaney, Claire, Sulaiman, Ahmad Hatim, Suominen, Kirsi, Suwalska, Aleksandra, Tam, Peter, Tatebayashi, Yoshitaka, Tondo, Leonardo, Vieta, Eduard, Vinberg, Maj, Viswanath, Biju, Volkert, Julia, Zetin, Mark, Zorrilla, Iñaki, Whybrow, Peter C., and Bauer, Michael

Published
2017
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48. Postępy w onkologii obliczeniowej i spersonalizowanej medycynie. T. 1, Tu i teraz!

Author

Bartnicka, Joanna, Prażuch, Wojciech, Bobek, Jarosław, Deorowicz, Sebastian, Długosz, Maciej, Dylong, Mariola, Foszner, Paweł, Garbowska, Iga, Gładys, Bartłomiej, Gorzkowska, Agnieszka, Hermansa, Marek, Hoeftmann, Magdalena, Hudecki, Andrzej, Hybiak, Jolanta, Jaksik, Roman, Jankowska, Kornelia, Jastrząb, Tomasz, Jóźwik-Wabik, Piotr, Jurkojć, Jacek, Kalisz, Seweryn, Kimmel, Marek, Kokot, Marek, Kręcichwost, Michał, Kuś, Paweł, Latos, Magdalena, Łopata, Karolina, Łos, Marek J., Macha, Dawid, Majchrzak, Ewa, Marczyk, Michał, Moćko, Natalia, Molik, Karolina, Pendziałek, Paweł, Piasecka-Belkhayat, Alicja, Polańska, Joanna, Popowicz, Adam, Polański, Andrzej, Różycka, Jagoda, Sage, Agata, Salinger, Julia, Skorupa, Anna, Siwek, Sławomir, Socha, Marek, Stryczyński, Mikołaj, Strzoda, Tomasz, Suwalska, Aleksandra, Szema, Aleksandra, Twardzik, Justyna, Więcławek, Wojciech, Wodarski, Piotr, Zdanowska, Iga, Żak, Weronika, POLCOVID Study Group, Bajkacz, Sylwia. Red., Ostrowski, Ziemowit. Red., and Polańska, Joanna. Red. serii

Subjects
bioinformatyka, rehabilitacja, neurologia, angiografia, biotechnologia medyczna, biomechanika, medycyna precyzyjna, przetwarzanie obrazów medycznych, medycyna spersonalizowana, obrazowanie medyczne, inżynieria biomedyczna, onkologia obliczeniowa, biomateriały w medycynie, radiografia, diagnostyka medyczna, informatyka obrazowania, onkologia, rentgenografia
Published
2021

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