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Clinical reasoning in traditional medicine exemplified by the clinical encounter of Korean medicine: a narrative review
No full textBackground
Clinical reasoning is generally defined as a way of thinking about diagnostic or therapeutic decision making in clinical practice. Different cognitive models have been proposed for the clinical reasoning process which takes place during the clinical encounter with a patient. This may have similarities with similar approaches used in Traditional Korean Medicine (TKM). Jinchal, the clinical encounter, has specific features in TKM and different Jinchal processes are closely related to several underlying cognitive models in clinical reasoning. It is a necessary process to see the patient, but in TKM, the method has characteristic aspects which should be evaluated based on the principle of clinical reasoning.
Methods
To obtain a narrative description and explanation of the concept of the Jinchal process, literature from with four authentic KM schools was explored first and expert panel discussion was conducted.
Results
This article analyses the Jinchal process using theoretical concepts from four authentic KM schools of clinical reasoning which are currently used in contemporary practice.
Conclusion
Future research should focus on the similarities and differences in understanding clinical reasoning in KM as well as the broader field of traditional East Asian Medicine.publishedVersio
Longitudinal assessments of child growth: A six-year follow-up of a cluster-randomized maternal education trial
Get PDFBackground & aims
Child growth impairments are rampant in sub-Saharan Africa. To combat this important health problem, long-term follow-up studies are needed to examine possible benefits and sustainability of various interventions designed to correct inadequate child growth. Our aim was to perform a follow-up study of children aged 60–72 months whose mothers participated in a two-armed cluster-randomized education intervention trial lasting 6 months in rural Uganda when their children were 6–8 months old with data collection at 20–24 and at 36 months. The education focused on nutrition, hygiene, and child stimulation.
Methods
We measured growth using anthropometry converted to z-scores according to WHO guidelines. We also included assessments of body composition using bioimpedance. We used multilevel mixed effect linear regression models with maximum likelihood method, unstructured variance-covariance structure, and the cluster as a random effect component to compare data from the intervention (receiving the education and routine health care) with the control group (receiving only routine health care).
Results
Of the 511 children included in the original trial, data from 166/263 (63%) and 141/248 (57%) of the children in the intervention and control group, respectively, were available for the current follow-up study. We found no significant differences in any anthropometrical z-score between the two study groups at child age of 60–72 months, except that children in the intervention group had lower (P = 0.006) weight-for-height z-score than the controls. There were no significant differences in the trajectories of z-scores or height growth velocity (cm/year) from baseline (start of original trial) to child age of 60–72 months. Neither did we detect any significant difference between the intervention and control group regarding body composition (fat mass, fat free mass, and total body water) at child age 60–72 months. Separate gender analyses had no significant impact on any of the growth or body composition findings.
Conclusion
In this long-term study of children participating in a randomized maternal education trial, we found no significant impact of the intervention on anthropometrical z-scores, height growth velocity or body composition.publishedVersio
The association between dietary diversity and development among children under 24 months in rural Uganda: Analysis of a cluster-randomised maternal education trial
No full textacceptedVersio
Secure Collaborative Augmented Reality Framework for Biomedical Informatics
Get PDFAugmented reality is currently a great interest in biomedical health informatics. At the same time, several challenges have been appeared, in particular with the rapid progress of smart sensors technologies, and medical artificial intelligence. This yields the necessity of new needs in biomedical health informatics. Collaborative learning and privacy are some of the challenges of augmented reality technology in biomedical health informatics. This paper introduces a novel secure collaborative augmented reality framework for biomedical health informatics-based applications. Distributed deep learning is first performed across a multi-agent system platform. The privacy strategy is developed for ensuring better communications of the different intelligent agents in the system. In this research work, a system of multiple agents is created for the simulation of the collective behaviours of the smart components of biomedical health informatics. Augmented reality is also incorporated for better visualization of the resulted medical patterns. A novel privacy strategy based on blockchain is investigated for ensuring the confidentiality of the learning process. Experiments are conducted on the real use case of the biomedical segmentation process. Our strong experimental analysis reveals the strength of the proposed framework when directly compared to state-of-the-art biomedical health informatics solutions.submittedVersio
Sensor data fusion for the industrial artificial intelligence of things
Get PDFThe emergence of smart sensors, artificial intelligence, and deep learning technologies yield artificial intelligence of things, also known as the AIoT. Sophisticated cooperation of these technologies is vital for the effective processing of industrial sensor data. This paper introduces a new framework for addressing the different challenges of the AIoT applications. The proposed framework is an intelligent combination of multi-agent systems, knowledge graphs and deep learning. Deep learning architectures are used to create models from different sensor-based data. Multi-agent systems can be used for simulating the collective behaviours of the smart sensors using IoT settings. The communication among different agents is realized by integrating knowledge graphs. Different optimizations based on constraint satisfaction as well as evolutionary computation are also investigated. Experimental analysis is undertaken to compare the methodology presented to state-of-the-art AIoT technologies. We show through experimentation that our designed framework achieves good performance compared to baseline solutions.publishedVersio
Tobacco use and risk factors for hypertensive individuals in Kenya
Get PDFThis study aimed to examine the association between hypertension and tobacco use as well as other known hypertensive risk factors (BMI, waist–hip ratio, alcohol consumption, physical activity, and socio-economic factors among adults) in Kenya. The study utilized the 2015 Kenya STEPs survey (adults aged 18–69) and investigated the association between tobacco use and hypertension. Descriptive statistics, correlation, frequencies, and regression (linear and logistic) analyses were used to execute the statistical analysis. The study results indicate a high prevalence of hypertension in association with certain risk factors—body mass index (BMI), alcohol, waist–hip ratio (WHR), and tobacco use—that were higher in males than females among the hypertensive group. Moreover, the findings noted an exceptionally low awareness level of hypertension in the general population. BMI, age, WHR, and alcohol use were prevalent risks of all three outcomes: hypertension, systolic blood pressure, and diastolic blood pressure. Healthcare authorities and policymakers can employ these findings to lower the burden of hypertension by developing health promotion and intervention policies.This research does not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. In-kind support, in terms of facilitating logistics, providing volunteers, providing IT access, and office space is being provided by the investigators’ host institutions.publishedVersio
Health Outcomes and Health Spending in the United States and the Nordic Countries
No full textpublishedVersio
Om offentlige anskaffelser
Get PDFAbstract: What the government purchases forms our daily routines and the world
that surrounds us. -e public sector can use its procurement to stimulate jobs and
to create an economy that is more innovative and sustainable. High-quality public
services depend on well-managed and professional procurement practitioners. Public procurement practitioners have an essential job to make e%ective and e.cient
decisions for our common money and act with integrity according to laws. Academically, research on public procurement in Norway is limited. -is anthology brings
together authors from di%erent areas to shed light on exciting research questions
in public procurement. -e anthology consists of 10 di%erent chapters that discuss
di%erent aspects of public procurement in Norway. Finally, implications regarding
future research and study will be discussed.publishedVersio
