Application of machine learning in predicting frailty syndrome in patients with heart failure.

Autor: Szczepanowski R; Department of Computer Science and Systems Engineering, Wroclaw University of Science and Technology, Poland., Uchmanowicz I; Department of Nursing and Obstetrics, Faculty of Health Sciences, Wroclaw Medical University, Poland.; Institute of Heart Diseases, University Hospital, Wrocław, Poland., Pasieczna-Dixit AH; Socio-Economic Department, Pomeranian Higher School, Starogard Gdański, Poland., Sobecki J; Department of Computer Science and Systems Engineering, Wroclaw University of Science and Technology, Poland., Katarzyniak R; Department of Computer Science and Systems Engineering, Wroclaw University of Science and Technology, Poland., Kołaczek G; Department of Computer Science and Systems Engineering, Wroclaw University of Science and Technology, Poland., Lorkiewicz W; Department of Computer Science and Systems Engineering, Wroclaw University of Science and Technology, Poland., Kędras M; Department of Computer Science and Systems Engineering, Wroclaw University of Science and Technology, Poland., Dixit A; Department of Computer Science and Systems Engineering, Wroclaw University of Science and Technology, Poland., Biegus J; Institute of Heart Diseases, University Hospital, Wrocław, Poland.; Institute for Heart Diseases, Wroclaw Medical University, Poland., Wleklik M; Department of Nursing and Obstetrics, Faculty of Health Sciences, Wroclaw Medical University, Poland.; Institute of Heart Diseases, University Hospital, Wrocław, Poland., Gobbens RJJ; Faculty of Health, Sports and Social Work, Inholland University of Applied Sciences, Amsterdam, the Netherlands.; Zonnehuisgroep Amstelland, Amstelveen, the Netherlands., Hill L; Department Family Medicine and Population Health, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium., Jaarsma T; Tranzo, Tilburg University, the Netherlands., Hussain A; School of Computing, Edinburgh Napier University, UK., Barbagallo M; Geriatric Unit, Department of Internal Medicine and Geriatrics, University of Palermo, Italy., Veronese N; Geriatric Unit, Department of Internal Medicine and Geriatrics, University of Palermo, Italy., Morabito FC; Mediterranea University of Reggio Calabria (DICEAM), Italy., Kahsin A; Faculty of Medicine, Medical University of Gdansk, Poland.

Publikováno v: Advances in clinical and experimental medicine : official organ Wroclaw Medical University [Adv Clin Exp Med] 2024 Mar; Vol. 33 (3), pp. 309-315.

Importance analysis of psychosociological variables in frailty syndrome in heart failure patients using machine learning approach.

Autor: Pasieczna AH; University of Lower Silesia DSW, Wrocław, Poland., Szczepanowski R; Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wroclaw University of Science and Technology, Wyb. Wyspiańskiego 27, 50-370, Wroclaw, Poland. remigiusz.szczepanowski@pwr.edu.pl., Sobecki J; Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wroclaw University of Science and Technology, Wyb. Wyspiańskiego 27, 50-370, Wroclaw, Poland., Katarzyniak R; Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wroclaw University of Science and Technology, Wyb. Wyspiańskiego 27, 50-370, Wroclaw, Poland., Uchmanowicz I; Department of Nursing and Obstetrics, Faculty of Health Sciences, Wroclaw Medical University, Wroclaw, Poland., Gobbens RJJ; Faculty of Health, Sports and Social Work, Inholland University of Applied Sciences, Amsterdam, the Netherlands.; Department Family Medicine and Population Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium.; Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, the Netherlands.; Zonnehuisgroep Amstelland, Amstelveen, the Netherlands., Kahsin A; Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland., Dixit A; Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wroclaw University of Science and Technology, Wyb. Wyspiańskiego 27, 50-370, Wroclaw, Poland.

Publikováno v: Scientific reports [Sci Rep] 2023 May 13; Vol. 13 (1), pp. 7782. Date of Electronic Publication: 2023 May 13.

Opportunistic osteoporosis screening using routine computed tomography images to identify bone loss in gynecologic cancer survivors.

Autor: Sobecki J; Department of Obstetrics and Gynecology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA janelle.sobecki@wisc.edu., Weigman B; University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA., Anderson-Carter I; University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA., Barroilhet L; Department of Obstetrics and Gynecology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA., Chandereng T; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA., Kliewer M; Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA., Hartenbach E; Department of Obstetrics and Gynecology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA.

Publikováno v: International journal of gynecological cancer : official journal of the International Gynecological Cancer Society [Int J Gynecol Cancer] 2022 Aug 01; Vol. 32 (8), pp. 1050-1055. Date of Electronic Publication: 2022 Aug 01.

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