• MeSH
• algoritmy MeSH
• management nemoci MeSH
• Parkinsonova nemoc terapie   MeSH
• rozhodovací stromy MeSH
• zajištění kvality zdravotní péče MeSH
• Publikační typ
• souborné dílo MeSH

• Konspekt
• Patologie. Klinická medicína
• NLK Obory
• neurologie

• MeSH
• algoritmy MeSH
• management nemoci MeSH
• neuroprotektivní látky terapeutické užití   MeSH
• nutriční terapie MeSH
• Parkinsonova nemoc diagnóza   farmakoterapie   chirurgie   MeSH
• parkinsonské poruchy komplikace   MeSH
• rozhodovací stromy MeSH
• Publikační typ
• směrnice MeSH

• Konspekt
• Patologie. Klinická medicína
• NLK Obory
• neurologie
• neurochirurgie
• farmacie a farmakologie

Aim: The aim of the survey is to identify factors of the work environment which are important for general nurses when they are considering whether or not to leave their current employer. Design: The research consists of an observational and a crosssectional study. Methods: Based on a modified interpretation of Herzberg's theory, we created a structured interview to investigate environmental factors. Interviewers carried out 1,992 interviews with hospital nurses working in the Czech Republic, between 2011 and 2012. The data gathered were analyzed with data mining tools – a decision tree and nonparametric tests. Results: If a good opportunity arose, 34.7% of nurses would leave their current employer. The analysis of the decision tree identified the factor “Patient care”, i.e. a factor concerning the nature of the work itself, as the most important. Data mining offers a new view of the data and can reveal valuable information existing within the primary data. Conclusion: Data mining has great potential in nursing. In this research, the decision tree shows that the essence of the nursing profession is the nursing work itself and it is also the most significant stabilizing factor. The management of healthcare providers should create and maintain a work environment which will ensure nursing work can be performed without impediment, thus minimizing staff turnover.

• MeSH
• data mining MeSH
• lidé MeSH
• motivace MeSH
• mzdy a přídavky MeSH
• péče o pacienta psychologie   MeSH
• pracovní stres MeSH
• pracovní uspokojení * MeSH
• rozhodovací stromy MeSH
• zaměstnanost MeSH
• zdravotní sestry * ekonomika   klasifikace   psychologie   statistika a číselné údaje   MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• pozorovací studie MeSH
• práce podpořená grantem MeSH

• Publikační typ
• souhrny MeSH

OBJECTIVES: To develop a gadolinium-free MRI-based diagnosis prediction decision tree (DPDT) for adult-type diffuse gliomas and to assess the added value of gadolinium-based contrast agent (GBCA) enhanced images. MATERIALS AND METHODS: This study included preoperative grade 2-4 adult-type diffuse gliomas (World Health Organization 2021) scanned between 2010 and 2021. The DPDT, incorporating eleven GBCA-free MRI features, was developed using 18% of the dataset based on consensus readings. Diagnosis predictions involved grade (grade 2 vs. grade 3/4) and molecular status (isocitrate dehydrogenase (IDH) and 1p/19q). GBCA-free diagnosis was predicted using DPDT, while GBCA-enhanced diagnosis included post-contrast images. The accuracy of these predictions was assessed by three raters with varying experience levels in neuroradiology using the test dataset. Agreement analyses were applied to evaluate the prediction performance/reproducibility. RESULTS: The test dataset included 303 patients (age (SD): 56.7 (14.2) years, female/male: 114/189, low-grade/high-grade: 54/249, IDH-mutant/wildtype: 82/221, 1p/19q-codeleted/intact: 34/269). Per-rater GBCA-free predictions achieved ≥ 0.85 (95%-CI: 0.80-0.88) accuracy for grade and ≥ 0.75 (95%-CI: 0.70-0.80) for molecular status, while GBCA-enhanced predictions reached ≥ 0.87 (95%-CI: 0.82-0.90) and ≥ 0.77 (95%-CI: 0.71-0.81), respectively. No accuracy difference was observed between GBCA-free and GBCA-enhanced predictions. Group inter-rater agreement was moderate for GBCA-free (0.56 (95%-CI: 0.46-0.66)) and substantial for GBCA-enhanced grade prediction (0.68 (95%-CI: 0.58-0.78), p = 0.008), while substantial for both GBCA-free (0.75 (95%-CI: 0.69-0.80) and GBCA-enhanced (0.77 (95%-CI: 0.71-0.82), p = 0.51) molecular status predictions. CONCLUSION: The proposed GBCA-free diagnosis prediction decision tree performed well, with GBCA-enhanced images adding little to the preoperative diagnostic accuracy of adult-type diffuse gliomas. KEY POINTS: Question Given health and environmental concerns, is there a gadolinium-free imaging protocol to preoperatively evaluate gliomas comparable to the gadolinium-enhanced standard practice? Findings The proposed gadolinium-free diagnosis prediction decision tree for adult-type diffuse gliomas performed well, and gadolinium-enhanced MRI demonstrated only limited improvement in diagnostic accuracy. Clinical relevance Even inexperienced raters effectively classified adult-type diffuse gliomas using the gadolinium-free diagnosis prediction decision tree, which, until further validation, can be used alongside gadolinium-enhanced images to respect standard practice, despite this study showing that gadolinium-enhanced images hardly improved diagnostic accuracy.

• MeSH
• dospělí MeSH
• gadolinium MeSH
• gliom * diagnostické zobrazování   MeSH
• kontrastní látky * MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie * metody   MeSH
• nádory mozku * diagnostické zobrazování   MeSH
• prediktivní hodnota testů MeSH
• reprodukovatelnost výsledků MeSH
• rozhodovací stromy * MeSH
• senioři MeSH
• stupeň nádoru * MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

• MeSH
• algoritmy MeSH
• fuzzy logika * MeSH
• heuristika fyziologie   MeSH
• lidé MeSH
• metody pro podporu rozhodování MeSH
• pravděpodobnost MeSH
• rozhodovací stromy * MeSH
• rozhodování fyziologie   MeSH
• teoretické modely MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The increasing trend of adolescents' emotional symptoms has become a global public health problem. Especially, adolescents with chronic diseases or disabilities face more risks of emotional problems. Ample evidence showed family environment associates with adolescents' emotional health. However, the categories of family-related factors that most strongly influence adolescents' emotional health remained unclear. Additionally, it was not known that whether family environment influences emotional health differently between normally developed adolescents and those with chronic condition(s). Health Behaviours in School-aged Children (HBSC) database provides mass data about adolescents' self-reported health and social environmental backgrounds, which offers opportunities to apply data-driven approaches to determine critical family environmental factors that influence adolescents' health. Thus, based on the national HBSC data in the Czech Republic collected from 2017 to 2018, the current study adopted a data-driven method, classification-regression-decision-tree analysis, to investigate the impacts of family environmental factors, including demographic factors and psycho-social factors on adolescents' emotional health. The results suggested that family psycho-social functions played a significant role in maintaining adolescents' emotional health. Both normally developed adolescents and chronic-condition(s) adolescents benefited from communication with parents, family support, and parental monitoring. Besides, for adolescents with chronic condition(s), school-related parental support was also meaningful for decreasing emotional problems. In conclusion, the findings suggest the necessity of interventions to strengthen family-school communication and cooperation to improve chronic-disease adolescents' mental health. The interventions aiming to improve parent-adolescent communication, parental monitoring, and family support are essential for all adolescents.

• MeSH
• chronická nemoc MeSH
• dítě MeSH
• duševní zdraví * MeSH
• emoce MeSH
• lidé MeSH
• mladiství MeSH
• rodiče * psychologie   MeSH
• rozhodovací stromy MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• mladiství MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Recent studies, including the TENSION trial, support the use of endovascular thrombectomy (EVT) in acute ischemic stroke with large infarct (Alberta Stroke Program Early Computed Tomography Score (ASPECTS) 3-5). OBJECTIVE: To evaluate the cost-effectiveness of EVT compared with best medical care (BMC) alone in this population from a German healthcare payer perspective. METHODS: A short-term decision tree and a long-term Markov model (lifetime horizon) were used to compare healthcare costs and quality-adjusted life years (QALYs) between EVT and BMC. The effectiveness of EVT was reflected by the 90-day modified Rankin Scale (mRS) outcome from the TENSION trial. QALYs were based on published mRS-specific health utilities (EQ-5D-3L indices). Long-term healthcare costs were calculated based on insurance data. Costs (reported in 2022 euros) and QALYs were discounted by 3% annually. Cost-effectiveness was assessed using incremental cost-effectiveness ratios (ICERs). Deterministic and probabilistic sensitivity analyses were performed to account for parameter uncertainties. RESULTS: Compared with BMC, EVT yielded higher lifetime incremental costs (€24 257) and effects (1.41 QALYs), resulting in an ICER of €17 158/QALY. The results were robust to parameter variation in sensitivity analyses (eg, 95% probability of cost-effectiveness was achieved at a willingness to pay of >€22 000/QALY). Subgroup analyses indicated that EVT was cost-effective for all ASPECTS subgroups. CONCLUSIONS: EVT for acute ischemic stroke with established large infarct is likely to be cost-effective compared with BMC, assuming that an additional investment of €17 158/QALY is deemed acceptable by the healthcare payer.

• MeSH
• analýza nákladů a výnosů * metody   MeSH
• endovaskulární výkony * ekonomika   metody   MeSH
• ischemická cévní mozková příhoda * ekonomika   chirurgie   epidemiologie   MeSH
• kvalitativně upravené roky života MeSH
• lidé MeSH
• Markovovy řetězce * MeSH
• rozhodovací stromy * MeSH
• senioři MeSH
• trombektomie * ekonomika   metody   MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Německo MeSH

Implantology is rapidly developing interdisciplinary field providing enormous amounts of data to be classified, evaluated and interpreted. The analysis of clinical data remains a big challenge, because each new system has specific requirements. The aim of study was prepare specific tool for treatment planning. Decision support system is built on Expert system. It is interactive software which provides clinical recommendations and treatment planning. Expert systems are knowledge-based computer programs designed to provide assistance in diagnosis and treatment planning. These systems are used for health care (dentistry, medicine, pharmacy etc.). The application contained the medical history analysis to obtaining information useful in formulating a diagnosis and providing implant insertion and prosthetic reconstruction to the patient; the diagnostic examination of dental implant procedure; implant positioning diagnosis – 3-D measurement; diagnostic information for treatment planning; treatment plan in the form of objective measurement of implant placement that helps surgeon and prosthodontics. The decision algorithm implemented by programming language is used. Core of program is an expert knowledge programming like a decision tree. The analysis of the decision-making process for implant treatment in general practice is prepared and analyzed.

• MeSH
• implantace zubů MeSH
• lidé MeSH
• stomatologická protetika * trendy   MeSH
• systémy pro podporu klinického rozhodování * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH

• MeSH
• finanční podpora výzkumu jako téma MeSH
• lidé MeSH
• městské obyvatelstvo MeSH
• postoj ke zdraví MeSH
• rizikové faktory MeSH
• socioekonomické faktory MeSH
• stupeň vzdělání MeSH
• zdravotní stav MeSH
• životní styl MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• srovnávací studie MeSH