HeartBIT_4.0 - Application of innovative Medical Data Science technologies for heart diseases.

Project Information

HEARTBIT_4.0

Grant agreement ID: 857446

DOI 10.3030/857446

Project closed

EC signature date 11 July 2019

Start date 1 January 2020

End date 31 December 2022

Funded under

• Twinning of research institutions

Total cost € 787 825,25

EU contribution € 787 825,25

Coordinated by

UNIWERSYTET MEDYCZNY IM PIASTOW SLASKICH WE WROCLAWIU
Poland

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Websites, patent fillings, videos etc. (4)

Preparation of scientific manuscripts and presentations for congresses including

Preparation of scientific manuscripts and presentations for congresses including . After 18

Summer school

Summer school Delivery date 3436

Participation in brokerage meetings across Europe

Participation in brokerage meetings across Europe Delivery date 3436

The website and social-media profiles, posters, leaflets and other materials

Documents, reports (4)

Educational activities (lectures, laboratories and workshops) finished with reports

Educational activities (lectures, laboratories and workshops) finished with reports. Delivery date: 1-15

Course materials
Lecture and Workshop Content (for four frontal lectures and team projects)

Lecture and Workshop Content (for four frontal lectures and team projects). Months: 7,13,15,20,24,28

Workshop and lectures materials and Report from training.

Workshop and lectures materials and Report from training. Delivery date: 12,24,30

Publications

Peer reviewed articles (9)

An artificial intelligence approach to guiding the management of heart failure patients using predictive models: a systematic review

Author(s): Mikołaj Błaziak, Szymon Urban, Weronika Wietrzyk, Maksym Jura, Gracjan Iwanek, Bartłomiej Stańczykiewicz, Wiktor Kuliczkowski, Robert Zymliński, Maciej Pondel, Petr Berka, Dariusz Danel, Jan Biegus, Agnieszka Siennicka
Published in: Biomedicines, ISSN 2227-9059, 2022, ISSN 2227-9059
Publisher: MDPI
DOI: 10.3390/biomedicines10092188

Identification of risk groups for mental disorders, headache and oral behaviors in adults during the COVID-19 pandemic

Author(s): Mieszko Wieckiewicz, Dariusz Danel, Maciej Pondel, Joanna Smardz, Helena Martynowicz, Tomasz Wieczorek, Grzegorz Mazur, Robert Pudlo, Gniewko Wieckiewicz
Published in: Scientific Reports, Issue 11/1, 2021, ISSN 2045-2322
Publisher: Nature Publishing Group
DOI: 10.1038/s41598-021-90566-z

Machine learning approach to understand worsening renal function in acute heart failure

Author(s): Szymon Urban, Mikołaj Błaziak, Maksym Jura, Gracjan Iwanek, Barbara Ponikowska, Jolanta Horudko, Agnieszka Siennicka, Petr Berka, Jan Biegus, Piotr Ponikowski, Robert Zymliński
Published in: Biomolecules, Issue 12, 2022, Page(s) 1616, ISSN 2218-273X
Publisher: MDPI
DOI: 10.3390/biom12111616

Patterns of locus of control in people suffering from heart failure: an approach by clustering method

Author(s): Agnieszka Siennicka, Maciej Pondel, Szymon Urban, Ewa Anita Jankowska, Beata Ponikowska, Izabella Uchmanowicz
Published in: Medicina, 2022, ISSN 1010-660X
Publisher: Lietuvos Gydytoju Sajunga
DOI: 10.3390/medicina58111542

Novel phenotyping for acute heart failure - unsupervised machine learning-based approach

Author(s): Szymon Urban, Mikołaj Błaziak, Maksym Jura, Gracjan Iwanek, Agata Zdanowicz, Mateusz Guzik, Artur Borkowski, Piotr Gajewski, Jan Biegus, Agnieszka Siennicka, Maciej Pondel, Petr Berka, Piotr Ponikowski, Robert Zymliński
Published in: Biomedicines, 2022, ISSN 2227-9059
Publisher: MDPI
DOI: 10.3390/biomedicines10071514

Answering clinical questions using machine learning: should we look at diastolic blood pressure when tailoring blood pressure control?Autorzy?

Author(s): Maciej Siński, Petr Berka, Jacek Lewandowski, Piotr Sobieraj, Kacper Piechocki, Bartłomiej Paleczny, Agnieszka Siennicka
Published in: Journal of Clinical Medicine, 2022, ISSN 2077-0383
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/jcm11247454

The relationship between knowledge about the pandemic and willingness to get vaccinated against SARS-CoV-2 in medical students in Poland: a cross-sectional survey

Author(s): Aleksandra Jastrzębska, Gabrielle Saden, Brygida Knysz, Maciej Pondel, Agnieszka Siennicka
Published in: Frontiers in Public Health,, 2022, ISSN 2296-2565
Publisher: Frontiers
DOI: 10.3389/fpubh.2022.914462

A review of possible effects of cognitive biases on interpretation of rule-based machine learning models

Author(s): Tomáš Kliegr, Štěpán Bahník, Johannes Fürnkranz
Published in: Artificial Intelligence, Issue 295, 2021, Page(s) 103458, ISSN 0004-3702
Publisher: Elsevier BV
DOI: 10.1016/j.artint.2021.103458

Why was this cited? Explainable machine learning appliedto COVID‑19 research literature

Author(s): Lucie Beranová, Marcin P. Joachimiak, Tomáš Kliegr, Gollam Rabby, Vilém Sklenák
Published in: Scientometrics, 2022, ISSN 0138-9130
Publisher: Akademiai Kiado
DOI: 10.1007/s11192-022-04314-9