BACKGROUND: As the SARS-CoV-2 virus created a global pandemic and rapidly became an imminent threat to the health and lives of people worldwide, the need for a vaccine and its quick distribution among the population was evident. Due to the urgency, and on the back of international collaboration, vaccines were developed rapidly. However, vaccination rollouts showed different success rates in different countries and some also led to increased vaccine hesitancy. OBJECTIVE: The aim of this study was to identify the role of information sharing and context sensitivity in various vaccination programs throughout the initial COVID-19 vaccination rollout in different countries. Moreover, we aimed to identify factors in national vaccination programs related to COVID-19 vaccine hesitancy, safety, and effectiveness. Toward this end, multidisciplinary and multinational opinions from members of the Navigating Knowledge Landscape (NKL) network were analyzed. METHODS: From May to July 2021, 25 completed questionnaires from 27 NKL network members were collected. These contributors were from 17 different countries. The responses reflected the contributors' subjective viewpoints on the status and details of the COVID-19 vaccination rollout in their countries. Contributors were asked to identify strengths, weaknesses, opportunities, and threats (ie, SWOT) of the respective vaccination programs. The responses were analyzed using reflexive thematic analysis, followed by frequency analysis of identified themes according to the represented countries. RESULTS: The perspectives of NKL network members showed a link between organizational elements of the vaccination rollout and the accompanying societal response, both of which were related to strengths and weaknesses of the process. External sociocultural variables, improved public communication around vaccination-related issues, ethical controversies, and the spread of disinformation were the dominant themes related to opportunities and challenges. In the SWOT 2×2 matrix, Availability and Barriers emerged as internal categories, whereas Transparent communication and promotion and Societal divide emerged as key external categories. CONCLUSIONS: Inventory of themes and categories inspired by elements of the SWOT framework provides an informative multidisciplinary perspective for effective implementation of public health strategies in the battle against COVID-19 or any future pandemics of a similar nature.
- MeSH
- COVID-19 * epidemiologie MeSH
- komunikace MeSH
- lidé MeSH
- SARS-CoV-2 MeSH
- vakcinace MeSH
- vakcíny proti COVID-19 * terapeutické užití MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND AND AIMS: Right bundle branch block (RBBB) and resulting right ventricular (RV) electromechanical discoordination are thought to play a role in the disease process of subpulmonary RV dysfunction that frequently occur post-repair tetralogy of Fallot (ToF). We sought to describe this disease entity, the role of pulmonary re-valvulation, and the potential added value of RV cardiac resynchronization therapy (RV-CRT). METHODS: Two patients with repaired ToF, complete RBBB, pulmonary regurgitation, and significantly decreased RV function underwent echocardiography, cardiac magnetic resonance, and an invasive study to evaluate the potential for RV-CRT as part of the management strategy. The data were used to personalize the CircAdapt model of the human heart and circulation. Resulting Digital Twins were analysed to quantify the relative effects of RV pressure and volume overload and to predict the effect of RV-CRT. RESULTS: Echocardiography showed components of a classic RV dyssynchrony pattern which could be reversed by RV-CRT during invasive study and resulted in acute improvement in RV systolic function. The Digital Twins confirmed a contribution of electromechanical RV dyssynchrony to RV dysfunction and suggested improvement of RV contraction efficiency after RV-CRT. The one patient who underwent successful permanent RV-CRT as part of the pulmonary re-valvulation procedure carried improvements that were in line with the predictions based on his Digital Twin. CONCLUSION: An integrative diagnostic approach to RV dysfunction, including the construction of Digital Twins may help to identify candidates for RV-CRT as part of the lifetime management of ToF and similar congenital heart lesions.
- MeSH
- blokáda Tawarova raménka diagnostické zobrazování etiologie terapie MeSH
- dysfunkce pravé srdeční komory * diagnostické zobrazování etiologie terapie MeSH
- echokardiografie MeSH
- Fallotova tetralogie * diagnostické zobrazování chirurgie MeSH
- lidé MeSH
- počítačová simulace MeSH
- srdeční komory MeSH
- srdeční resynchronizační terapie * škodlivé účinky MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Data o zdravotní péči ve správě státem řízených organizací jsou pro společnost cenným nehmotným aktivem. Jejich využití by mělo být pro jejich správce a stát prioritou. Zcela paternalistický přístup správců a státu je nežádoucí, jakkoliv má za cíl ochranu práva na soukromí osob registrovaných v databázích. V souladu s evropskou politikou a celosvětovým trendem by však tato opatření neměla převážit společenský benefit, který z analýzy těchto údajů vyplývá, existují-li technické možnosti práva osob na soukromí dostatečně chránit. Česká společnost vede k tématu intenzivní diskusi, která se však podle autorů jen nedostatečně opírá o fakta a postrádá jasně artikulovaná stanoviska odborné veřejnosti. Cílem tohoto článku je tyto mezery zacelit. Techniky anonymizace údajů představují řešení, jak chránit práva jednotlivců na soukromí a zároveň zachovat vědeckou hodnotu údajů. Riziko ztotožnění jednotlivců v anonymizovaných souborech údajů je škálovatelné a lze ho minimalizovat v závislosti na typu a obsahu údajů a jejich použití konkrétním žadatelem. Nalezení optimální formy a rozsahu deidentifikovaných údajů vyžaduje kompetence a znalosti jak na straně žadatele, tak na straně správce. Je v zájmu žadatele, správce i chráněných osob v databázích, aby obě strany projevily ochotu a měly schopnost a odborné znalosti komunikovat v průběhu žádosti a jejího zpracování.
Healthcare data held by state-run organisations is a valuable intangible asset for society. Its use should be a priority for its administrators and the state. A completely paternalistic approach by administrators and the state is undesirable, however much it aims to protect the privacy rights of persons registered in databases. In line with European policies and the global trend, these measures should not outweigh the social benefit that arises from the analysis of these data if the technical possibilities exist to sufficiently protect the privacy rights of individuals. Czech society is having an intense discussion on the topic, but according to the authors, it is insufficiently based on facts and lacks clearly articulated opinions of the expert public. The aim of this article is to fill these gaps. Data anonymization techniques provide a solution to protect individuals' privacy rights while preserving the scientific value of the data. The risk of identifying individuals in anonymised data sets is scalable and can be minimised depending on the type and content of the data and its use by the specific applicant. Finding the optimal form and scope of deidentified data requires competence and knowledge on the part of both the applicant and the administrator. It is in the interest of the applicant, the administrator, as well as the protected persons in the databases that both parties show willingness and have the ability and expertise to communicate during the application and its processing.
In this article, we introduce a new approach to human movement by defining the movement as a static super object represented by a single two-dimensional image. The described method is applicable in remote healthcare applications, such as physiotherapeutic exercises. It allows researchers to label and describe the entire exercise as a standalone object, isolated from the reference video. This approach allows us to perform various tasks, including detecting similar movements in a video, measuring and comparing movements, generating new similar movements, and defining choreography by controlling specific parameters in the human body skeleton. As a result of the presented approach, we can eliminate the need to label images manually, disregard the problem of finding the start and the end of an exercise, overcome synchronization issues between movements, and perform any deep learning network-based operation that processes super objects in images in general. As part of this article, we will demonstrate two application use cases: one illustrates how to verify and score a fitness exercise. In contrast, the other illustrates how to generate similar movements in the human skeleton space by addressing the challenge of supplying sufficient training data for deep learning applications (DL). A variational auto encoder (VAE) simulator and an EfficientNet-B7 classifier architecture embedded within a Siamese twin neural network are presented in this paper in order to demonstrate the two use cases. These use cases demonstrate the versatility of our innovative concept in measuring, categorizing, inferring human behavior, and generating gestures for other researchers.
- Publikační typ
- časopisecké články MeSH
Současný technologický vývoj přispívá ke generování velkých objemů dat, která nelze vyhodnocovat pouze manuálně. Vývoj metod umělé inteligence a jejich aplikace v medicíně a zdravotnictví umožňuje podporu procesu péče o pacienta technologiemi a metodami analýzy dat. Existuje mnoho úspěšných aplikací, které pomáhají v procesu podpory rozhodování, zejména při zpracování komplexních vícerozměrných heterogenních a/nebo dlouhodobých dat. Na druhé straně se v aplikacích metod umělé inteligence objevují neúspěchy. V posledních letech se stalo velmi populární hluboké učení, které do jisté míry přináší slibné výsledky. Má však určité nedostatky, které mohou vést k chybné klasifikaci. V článku jsou stručně představeny správné metodické kroky při návrhu a implementaci vybraných metod pro zpracování dat.
The aim of the article to present the development of artificial intelligence (AI) methods and their applications in medicine and health care. Current technological development contributes to generation of large volumes of data that cannot be evaluated only manually. We describe the process of patient care and its individual parts that can be supported by technology and data analysis methods. There are many successful applications that help in the decision support process, in processing complex multidimensional heterogeneous and/or long-term data. On the other side, failures appear in AI methods applications. In recent years, deep learning became very popular and to a certain extend it delivered promising results. However, it has certain flaws that might lead to misclassification. The correct methodological steps in design and implementation of selected methods to data processing are briefly presented.
- MeSH
- lékařská informatika MeSH
- lidé MeSH
- umělá inteligence * dějiny MeSH
- veřejné zdravotnictví * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
Health conditions contribute significantly to patients' quality of life. Healthcare infrastructure and healthcare services, including their accessibility, belong to objective factors influencing their perception of their health. The growing disparity between supply and demand for specialized inpatient facilities due to the aging population calls for new solutions, including eHealth technologies. Automatized activities could be taken over by eHealth technologies that do not require a constant presence of staff. We tested whether eHealth technical solutions reduce patients' health risks on a sample of 61 patients on the covid-19 unit in Tomas Bata hospital in Zlin. We have applied the randomized control trial to select patients for the treatment and the control groups. Moreover, we tested eHealth technologies and their help to staff in the hospital. Due to the severity of the covid-19 disease and its rapid course and the size of the sample in our research, we did not demonstrate a statistically significant impact of eHealth technologies on patient health. The evaluation results confirm that even the limited number of technologies deployed proves to be an effective help for staff in critical situations like the pandemic. The main issue is psychological support to staff in hospitals and relieving stressful work.
- MeSH
- COVID-19 * MeSH
- hodnocení programu MeSH
- kvalita života MeSH
- lidé MeSH
- nemocnice MeSH
- senioři MeSH
- telemedicína * MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- hodnotící studie MeSH
Hydration plays a very important role in old age. This is because hydration changes over the course of life and therefore geriatric patients need to have their hydration monitored. However, the general problem is that there are no completely reliable methods' that can measure this. In this paper we performed a pilot monitoring in geriatric patients and compared directly measured electrical data with results from biochemistry. The observed correlations on our pilot sample show very promising values for (r=0.68) creatinine correlation with phase angle and (r=0.71) creatinine correlation with NI (nutritional index). It also shows that electrical readings may in the future indicate much more accurately the true status of the patient. Our research is still ongoing, and we are planning further measurements on a larger sample.
- MeSH
- elektrická impedance MeSH
- hodnocení stavu výživy * MeSH
- kreatinin MeSH
- lidé MeSH
- longitudinální studie MeSH
- pilotní projekty MeSH
- senioři MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: Phase-contrast MRI allows detailed measurements of various parameters of CSF motion. This examination is technically demanding and machine dependent. The literature on this topic is ambiguous. Machine learning (ML) approaches have already been successfully utilized in medical research, but none have yet been applied to enhance the results of CSF flowmetry. The aim of this study was to evaluate the possible contribution of ML algorithms in enhancing the utilization and results of MRI flowmetry in idiopathic normal pressure hydrocephalus (iNPH) diagnostics. METHODS: The study cohort consisted of 30 iNPH patients and 15 healthy controls examined on one MRI machine. All major phase-contrast parameters were inspected: peak positive, peak negative, and average velocities; peak amplitude; positive, negative, and average flow rates; and aqueductal area. The authors applied ML algorithms to 85 complex features calculated from a phase-contrast study. RESULTS: The most distinctive parameters with p < 0.005 were the peak negative velocity, peak amplitude, and negative flow. From the ML algorithms, the Adaptive Boosting classifier showed the highest specificity and best discrimination potential overall, with 80.4% ± 2.9% accuracy, 72.0% ± 5.6% sensitivity, 84.7% ± 3.8% specificity, and 0.812 ± 0.047 area under the receiver operating characteristic curve (AUC). The highest sensitivity was 85.7% ± 5.6%, reached by the Gaussian Naive Bayes model, and the best AUC was 0.854 ± 0.028 by the Extra Trees classifier. CONCLUSIONS: Feature extraction algorithms combined with ML approaches simplify the utilization of phase-contrast MRI. The highest-performing ML algorithm was Adaptive Boosting, which showed good calibration and discrimination on the testing data, with 80.4% accuracy, 72.0% sensitivity, 84.7% specificity, and 0.812 AUC. Phase-contrast MRI boosted by the ML approach can help to determine shunt-responsive iNPH patients.
