Prediktor hmotnosti

• Název práce v češtině: Prediktor hmotnosti
• Název v anglickém jazyce: Weight Predictor
• Klíčová slova: Obezita, Telemedicína, Predikce hmotnosti, Vývoj hmotnosti, Self-monitoring
• Klíčová slova anglicky: Obesity, Telemedicine, Weight prediction, Weight development, Self-monitoring
• Akademický rok vypsání: 2022/2023
• Typ práce: diplomová práce
• Jazyk práce: čeština
• Ústav: III. interní klinika – klinika endokrinologie a metabolismu 1. LF UK a VFN (11-00530)
• Vedoucí / školitel: Mgr. Ondřej Kádě, Ph.D.
• Řešitel: skrytý - zadáno vedoucím/školitelem
• Datum přihlášení: 10.10.2022
• Datum zadání: 13.10.2022
• Datum a čas obhajoby: 15.06.2023 08:00
• Datum odevzdání elektronické podoby: 29.04.2023
• Datum proběhlé obhajoby: 15.06.2023
• Předmět: Obhajoba diplomové práce (B02793)
• Oponenti: RNDr. Luděk Šefc, CSc.
• Konzultanti: prof. MUDr. Martin Matoulek, Ph.D.

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Předběžná náplň práce

Diplomová práce se zabývá faktory, které ovlivňují redukci hmotnosti, pozornost je věnována věku a míře spolupráce, která je definována procentuálním počtem dnů, kdy pacienti zapsali jídelníček vůči celkovému počtu dnů ve výzkumu. Cílem práce je zodpovědět 2 hypotézy, tj. „Mladší pacient redukuje svou hmotnost snáze než starší pacient“ a „Spolupracující pacient redukuje svou hmotnost snadněji než nespolupracující pacient“ na základě analýzy dat monitorovaných pacientů. Data o jídelníčku, hmotnosti a pohybové aktivitě jsou self-monitorována a sbírána pomocí webových a mobilních aplikací, data o tělesném složení jsou sbírána na pravidelných nutričních konzultacích. Diplomová práce je psána v rámci projektu "Prediktor hmotnosti", jehož cílem je tvorba softwaru, jenž bude předpovídat vývoj hmotnosti v čase v reakci na provedené intervence.

Předběžná náplň práce v anglickém jazyce

The thesis focuses on the factors that influence weight loss, with attention paid to age and the level of cooperation, which is defined by the percentage of days that patients wrote down the diet in relation to the total number of days in the study. The aim of the study is to answer 2 hypotheses, i.e. "Younger patient reduces their weight more easily than older patient" and "Cooperating patient reduces their weight more easily than non-cooperating patient" based on the analysis of the data of monitored patients. Diet, weight, and physical activity data are self-monitored and collected using web and mobile apps, and body composition data are collected at regular nutritional consultations. The thesis is written as part of the "Weight Predictor" project, which aims to create software that will predict weight change over time in response to interventions.