Metal Organic Frameworks (MOFs) and ultrasound: A review.

Metal-organic frameworks (MOFs) have received a lot of attention due to their unique properties and abundant functionalities. Permanent porosity and high surface area are just a few traits that have made them attractive to researchers. They can be prepared as task-specific materials by exploiting the functional group variety and tuning their size and geometry. The main purpose of this review is to present an alternative method of preparing MOF crystals and underline the advantages of ultrasound assisted (sonochemical) synthesis. State of the art ultrasound assisted techniques for the preparation of MOFs in nanoscale are presented. Optimization of morphology and particle size is highlighted throughout this work, as we discuss the effects of various factors, such as energy input, reagent concentration, adequate solvents, reaction time and more.

Medical and Healthcare Curriculum Exploratory Analysis.

In the recent years, medical and healthcare higher education institutions compile their curricula in different ways in order to cover all necessary topics and sections that the students will need to go through to success in their future clinical practice. A medical and healthcare curriculum consists of many descriptive parameters, which define statements of what, when, and how students will learn in the course of their studies. For the purpose of understanding a complicated medical and healthcare curriculum structure, we have developed a web-oriented platform for curriculum management covering in detail formal metadata specifications in accordance with the approved pedagogical background, namely outcome-based approach. Our platform provides a rich database that can be used for innovative detailed educational data analysis. In this contribution we would like to present how we used a proven process model as a way of increasing accuracy in solving individual analytical tasks with the available data. Moreover, we introduce an innovative approach on how to explore a dataset in accordance with the selected methodology. The achieved results from the selected analytical issues are presented here in clear visual interpretations in an attempt to visually describe the entire medical and healthcare curriculum.

Using Competency-Based Digital Open Learning Activities to Facilitate and Promote Health Professions Education (OLAmeD): A Proposal.

BACKGROUND: Traditional learning in medical education has been transformed with the advent of information technology. We have recently seen global initiatives to produce online activities in an effort to scale up learning opportunities through learning management systems and massive open online courses for both undergraduate and continued professional education. Despite the positive impact of such efforts, factors such as cost, time, resources, and the specificity of educational contexts restrict the design and exchange of online medical educational activities. OBJECTIVE: The goal is to address the stated issues within the health professions education context while promoting learning by proposing the Online Learning Activities for Medical Education (OLAmeD) concept which builds on unified competency frameworks and generic technical standards for education. METHODS: We outline how frameworks used to describe a set of competencies for a specific topic in medical education across medical schools in the United States and Europe can be compared to identify commonalities that could result in a unified set of competencies representing both contexts adequately. Further, we examine how technical standards could be used to allow standardization, seamless sharing, and reusability of educational content. RESULTS: The entire process of developing and sharing OLAmeD is structured and presented in a set of steps using as example Urology as a part of clinical surgery specialization. CONCLUSIONS: Beyond supporting the development, sharing, and repurposing of educational content, we expect OLAmeD to work as a tool that promotes learning and sets a base for a community of medical educational content developers across different educational contexts.

Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.

BACKGROUND: No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution's curriculum, including tools for unveiling relationships inside curricular datasets. OBJECTIVE: We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. METHODS: We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom's taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. RESULTS: We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. CONCLUSIONS: We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.

Practical use of medical terminology in curriculum mapping.

BACKGROUND: Various information systems for medical curriculum mapping and harmonization have been developed and successfully applied to date. However, the methods for exploiting the datasets captured inside the systems are rather lacking. METHOD: We reviewed the existing medical terminologies, nomenclatures, coding and classification systems in order to select the most suitable one and apply it in delivering visual analytic tools and reports for the benefit of medical curriculum designers and innovators. RESULTS: A formal description of a particular curriculum of general medicine is based on 1347 learning units covering 7075 learning outcomes. Two data-analytical reports have been developed and discussed, showing how the curriculum is consistent with the MeSH thesaurus and how the MeSH thesaurus can be used to demonstrate interconnectivity of the curriculum through association analysis. CONCLUSION: Although the MeSH thesaurus is designed mainly to index medical literature and support searching through bibliographic databases, we have proved its use in medical curriculum mapping as being beneficial for curriculum designers and innovators. The presented approach can be followed wherever needed to identify all the mandatory components used for transparent and comprehensive overview of medical curriculum data.

Visual analytics in medical education: impacting analytical reasoning and decision making for quality improvement.

The medical curriculum is the main tool representing the entire undergraduate medical education. Due to its complexity and multilayered structure it is of limited use to teachers in medical education for quality improvement purposes. In this study we evaluated three visualizations of curriculum data from a pilot course, using teachers from an undergraduate medical program and applying visual analytics methods. We found that visual analytics can be used to positively impacting analytical reasoning and decision making in medical education through the realization of variables capable to enhance human perception and cognition on complex curriculum data. The positive results derived from our evaluation of a medical curriculum and in a small scale, signify the need to expand this method to an entire medical curriculum. As our approach sustains low levels of complexity it opens a new promising direction in medical education informatics research.

AUVA - Augmented Reality Empowers Visual Analytics to explore Medical Curriculum Data.

Medical curriculum data play a key role in the structure and the organization of medical programs in Universities around the world. The effective processing and usage of these data may improve the educational environment of medical students. As a consequence, the new generation of health professionals would have improved skills from the previous ones. This study introduces the process of enhancing curriculum data by the use of augmented reality technology as a management and presentation tool. The final goal is to enrich the information presented from a visual analytics approach applied on medical curriculum data and to sustain low levels of complexity of understanding these data.

OPTIMED Platform: Curriculum Harmonisation System for Medical and Healthcare Education.

This contribution introduces a new web-based OPTIMED platform for an effective harmonisation of medical and healthcare curriculum. Behind the engineering background stays an original methodology covering planning model based on formal parameterisation of curriculum, which fully support the outcome-based approach to education. With the use of developed system curriculum, designers and senior guarantors can provide a clear and transparent composition of compulsory and optional courses, and easily identify potential duplicities and overlaps across a domain of medical and healthcare education. For students, it means an absolutely new way of how to understand what is really taught during a learning period, including all necessary meta information. All members across the academic community are able to search and consequently display in detail the most important domains related to the particular year, term, course, medical discipline or topic. The presented solution significantly enhances the transparency and continuity of the environment in which the authors of the teaching materials as well as their consumers work daily. Suggestions for future improvements of the OPTIMED platform are discussed.

Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education.

Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education. Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them. Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i) learning outcomes and teaching methods, (ii) examination and learning outcomes, and (iii) teaching methods, learning outcomes, examination results, and gap analysis. Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to explore such data with possible future implications on healthcare education. It also opens a new direction in medical education informatics research.

Big data in medical informatics: improving education through visual analytics.

A continuous effort to improve healthcare education today is currently driven from the need to create competent health professionals able to meet healthcare demands. Limited research reporting how educational data manipulation can help in healthcare education improvement. The emerging research field of visual analytics has the advantage to combine big data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognise visual patterns. The aim of this study was therefore to explore novel ways of representing curriculum and educational data using visual analytics. Three approaches of visualization and representation of educational data were presented. Five competencies at undergraduate medical program level addressed in courses were identified to inaccurately correspond to higher education board competencies. Different visual representations seem to have a potential in impacting on the ability to perceive entities and connections in the curriculum data.